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Investigating the role of voltage-gated ion channels inpulsed electric field effects in excitable and non-excitable
cell linesRyan Burke
To cite this version:Ryan Burke. Investigating the role of voltage-gated ion channels in pulsed electric field effects inexcitable and non-excitable cell lines. Human health and pathology. Université de Limoges, 2017.English. �NNT : 2017LIMO0118�. �tel-01930812�
1
Université de Limoges École Doctorale Bio-Santé (ED 524)
Faculté de Sciences et Techniques – XLIM Équipe BioEM
Thèse pour obtenir le grade de
Docteur de l’Université de Limoges Discipline – Biologie, médicine et santé
Présentée et soutenue par
Ryan Burke
Le 19 décembre 2017
Thèse dirigée par Dr. Philippe Leveque
Co-dirigée par Dr. Sylvia Bardet
JURY :
Président du jury Mme. Catherine YARDIN Professeur des universités, Praticien hospitalier
Rapporteurs M. Justin TEISSIE Directeur de recherche CNRS, émérite M. Yann PERCHERANCIER Chargé de recherche CNRS, HDR
Examinateurs M. Mounir TAREK Directeur de recherche CNRS Mme Sylvia BARDET Maître de conférences, Université de Limoges M. Philippe LEVEQUE Directeur de recherche CNRS
Investigating the role of voltage-gated ion channels in pulsed electric field
effects in excitable and non-excitable cell lines
Thèse de doctorat
2
Structure of the thesis
All experiments described in this thesis were conducted over the period of 2014 – 2017.
They were carried out primarily in the Bioelectromagnetics lab at XLIM Research Institute in
Limoges, France. Another portion of the data presented in this thesis was the result of a
collaboration with the group at the Biocybernetics lab at the University of Ljubljana.
The thesis is outlined as follows:
Chapter 1 provides a review of the literature and describes the general methodology for
this thesis.
Chapter 2 is the first experimental section that employs advanced biostatistics to
examine how well data can be predicted using common parameters present in current
electrophysical models of electropermeabilization.
Chapter 3 looks at the effects of nanosecond pulsed electric fields on the
transmembrane potential in U87 glioblastoma cells. Using a host of pharmacological
modulators of ion channel activity, the role of voltage-gated ion channels is explored.
Chapter 4 is the result of a collaborative exchange with the University of Ljubljana. We
look at the effect of pulsed electric fields, ranging from 10 ns to 10 ms, on membrane
potential and membrane permeability of several cell lines.
Chapter 5 begins with a brief summary of each chapter, and then moves into a more
global discussion of how our results contribute to the current literature.
3
Acknowledgements
There are so many people that I wish to thank for their inspiration, support and guidance.
I would like to thank Dr. Michael Persinger who was my thesis supervisor during my
B.Sc. and M.Sc. candidacy. You have inspired me in ways you will never know. You
demanded excellence and creativity and pushed me to grow beyond what I imagined
possible. I am grateful, maybe above all, for your emphasis on developing a very strong
knowledge of biostatistics. There is no tool more important or more powerful in science than
the ability to properly measure and interpret experimental data.
Thank you to Dr. Philippe Leveque. Despite being overwhelmed with a tremendous
work load, you took me on as your student half way through my Ph.D. Thank you for all of
your guidance and support. If I could go back in time, I would have selected you as my
supervisor for my entire Ph.D.
I am grateful to several colleagues who I am happy to call friends. Lynn, Maarten and
Stine, you all have helped so much. What an honor to have worked with you. I wish you all
prosperity and happiness in your future endeavors.
Thank you to my amazing family. Mom, you are one of the most inspiring people I
have ever known. I am here because of you. Thank you for everything you have ever done for
your family. I cherish you. Dad, I can’t begin to express how much I miss you. You taught me
what it means to be a man. You taught me to pursue my dreams and to never give up. This
thesis is dedicated to your memory. Cancer took you from us, and I hope that my humble
contribution to the field of cancer research would have made you proud. Tom, you are such
an amazing brother. Although you’re my younger brother, I have always looked up to your
incredible work ethic. I am so proud of the man you have grown into. You deserve nothing
but excellence. Les, I hope you realize that I love you so much. You too are an amazing man
and I am so happy for you and your beautiful family. I have the best brothers ever! I love you
all!
4
To the love of my life, Melanie. You have no idea how much you mean to me. You put
all of your dreams on hold for me to be here today. When faced with the idea of selling
everything you own and flying across the ocean far away from your family friends, you didn’t
hesitate for one second. There is no luckier man than I. You are truly a remarkable woman! I
feel blessed for every moment we share and I look forward to the next chapter of our lives.
From the bottom of my heart, thank you.
5
Abstract (English)
The use of pulsed electric fields (PEF) in medical and biotechnology sectors has
become increasingly prevalent over the last few decades. Research has shown that by adjusting
the duration of the PEF we can predict what effects will be observed. Whereas PEF in the
micro-to-millisecond range have been used to permeabilize the cell membrane and enhance
drug or protein uptake, nanosecond PEF (nsPEF) have demonstrated unique effects on
intracellular organelles. Both PEF and nsPEF have demonstrated therapeutic potential for a
variety of human pathologies, including the treatment of cancer. Using live-cell imaging, this
thesis investigated, in vitro, the effects of pulsed fields ranging in duration from 10 ns to 10
ms on cancerous (U87 glioblastoma multiforme) and non-cancerous cell lines (mouse
hippocampal neurons (HT22) and Chinese hamster ovary (CHO) cells). Previously published
results have demonstrated that cancerous cells have a greater sensitivity to applied electric
fields than healthy cells do. Our results are in agreement with these findings, insofar as the
U87 cells underwent a significantly greater depolarization of their transmembrane potential
following a single electric pulse at all durations. In a parallel set of experiments, despite having
similar electric field thresholds for membrane permeabilization, the U87 cells demonstrated
significantly enhanced YO-PRO uptake compared to the other cells lines. Although U87 cells
underwent the greatest change in both membrane depolarization and membrane
permeabilization, they also showed the fastest membrane resealing constant, which was
approximately 30 seconds faster than other cell lines. To elucidate some of the underlying
mechanisms by which U87 cells respond to electric fields, a series of experiments looked at the
role of transmembrane ion channels. Several recent studies have reported that PEFs can act
directly on voltage-gated ion channels. Using a variety of specific and broad acting
pharmacological ion channel modulators, we demonstrated that we could almost entirely
inhibit the electric field-induced membrane depolarization in U87 cells by blocking certain
cationic channels. These results were quite specific, such that the big conductance potassium
(BK) channel, L- and T-type calcium channels, and the non-specific cationic channel, TRPM8,
were able to inhibit depolarization while blocking other ion channels produced no significant
6
change. The work in this thesis showed that the malignant U87 cell line showed a greater
sensitivity to electric fields from ranging from 10 ns – 10 ms when compared to the non-
cancerous cell lines that were investigated. Potential improvements to current treatment
protocols have been proposed based on the findings presented herein.
7
Résumé (Français)
L'utilisation de champs électriques pulsés (PEF) dans les secteurs de la médecine et de
la biotechnologie est devenue de plus en plus courante au cours des dernières décennies. La
recherche a montré qu'en ajustant la durée du PEF, nous pouvons prédire quels effets seront
observés. Alors que les PEF dans la gamme micro - milliseconde ont été utilisés pour
perméabiliser la membrane cellulaire et améliorer l'absorption de médicament ou de protéine,
le PEF nanoseconde (nsPEF) a démontré des effets uniques sur les organites intracellulaires.
Les deux PEF et nsPEF ont démontré un potentiel thérapeutique pour une variété de
pathologies humaines, y compris le traitement du cancer. Utilisant l'imagerie des cellules
vivantes, cette thèse a étudié in vitro les effets de champs pulsés d'une durée de 10 ns à 10 ms
sur des lignées cancéreuses (U87 glioblastome multiforme) et non cancéreuses (neurones
hippocampes de souris (HT22) et cellules ovariennes du hamster chinois (CHO)). Des
résultats publiés antérieurement ont démontré que les cellules cancéreuses sont plus sensibles
aux champs électriques que les cellules saines. Nos résultats sont en accord avec ces résultats,
dans la mesure où les cellules U87 ont subi une dépolarisation significativement plus
importante de leur potentiel transmembranaire après une seule impulsion électrique à toutes
les durées. Dans un ensemble d'expériences parallèles, malgré des seuils de champ électrique
similaires pour la perméabilisation membranaire, les cellules U87 ont démontré une
absorption significativement améliorée de YO-PRO par rapport aux autres lignées cellulaires.
Bien que les cellules U87 aient subi le plus grand changement dans la dépolarisation
membranaire et la perméabilisation membranaire, elles ont également montré la constante de
rescellement de la membrane la plus rapide, qui était environ 30 secondes plus rapide que les
autres lignées cellulaires. Pour élucider certains des mécanismes sous-jacents par lesquels les
cellules U87 répondent aux champs électriques, une série d'expériences a examiné le rôle des
canaux ioniques transmembranaires. Plusieurs études récentes ont rapporté que les PEF
peuvent agir directement sur les canaux ioniques voltage-dépendants. En utilisant divers
modulateurs de canaux ioniques pharmacologiques spécifiques et à action large, nous avons
8
démontré que nous pouvions presque entièrement inhiber la dépolarisation membranaire
induite par le champ électrique dans les cellules U87 en bloquant certains canaux cationiques.
Ces résultats étaient assez spécifiques, tels que le canal de potassium de grande conductance
(BK), les canaux calciques de type L et T, et le canal cationique non spécifique, TRPM8, étaient
capables d'inhiber la dépolarisation tandis que le blocage d'autres canaux ioniques ne
produisait aucun changement significatif. . Les travaux de cette thèse ont montré que la lignée
cellulaire maligne U87 présentait une plus grande sensibilité aux champs électriques allant de
10 ns à 10 ms par rapport aux lignées cellulaires non cancéreuses étudiées. Des améliorations
potentielles aux protocoles de traitement actuels ont été proposées sur la base des résultats
présentés ici.
9
Table of Contents
Structure of the thesis .......................................................................................................................... 2
Acknowledgements .............................................................................................................................. 3
Abstract (English) ................................................................................................................................ 5
Résumé (Français) ............................................................................................................................... 7
Table of figures ................................................................................................................................... 12
Chapter 1: General Introduction ................................................................................................ 15
1.1 Pulsed electric fields ..................................................................................................................... 16
1.2 Biological membranes ................................................................................................................. 16
1.3 Transmembrane proteins ............................................................................................................ 17
1.4 Describing the cell as an electrical circuit ................................................................................. 19
1.5 Electric field interaction with the cell membrane .................................................................... 20
1.6 Factors influencing outcome following membrane exposure to an electric field ................ 21
1.6 The role of pulse duration in PEF effects .................................................................................. 23
1.7 PEF effects and applications ....................................................................................................... 24
1.7.1 Irreversible electropermeabilization (IRE) ........................................................................ 24
1.7.2 Reversible electropermeabilization .................................................................................... 24
1.8 nsPEF effects and applications .................................................................................................. 25
1.9 Limitations of PEF/nsPEF as a clinical treatment .................................................................. 28
1.10 General methods ........................................................................................................................ 28
1.11 Culture and maintenance of cell lines ...................................................................................... 29
1.11.1 Cell lines and maintenance ................................................................................................. 29
1.11.2 Differentiation of HT22 cells.............................................................................................. 30
1.12 Exposure of cells to electric pulses ........................................................................................... 30
1.13 Fluorescence imaging ................................................................................................................ 32
1.14 Fluorescent indicators for measuring transmembrane potential and membrane
permeability ........................................................................................................................................ 33
1.14.1 Measuring membrane permeability .................................................................................. 33
1.14.2 Measuring transmembrane potential ............................................................................... 34
1.15 Image acquisition ....................................................................................................................... 38
1.16 Statistical analysis ...................................................................................................................... 39
1.16.1 Independence of data .......................................................................................................... 39
1.16.2 Normal distribution ............................................................................................................ 40
1.16.3 Homogeneity of variance ................................................................................................... 40
1.16.4 Violations of statistical assumptions ................................................................................ 40
10
1.16.5 Additional inclusionary criteria......................................................................................... 41
1.16.6 Definition of threshold ....................................................................................................... 41
1.16.7 Statistical terminology and abbreviations ....................................................................... 41
1.17 Objectives and hypotheses for this Thesis ............................................................................... 42
Chapter 2: A comparative analysis of the theoretical and experimental interactions of PEF
with cells in vitro ................................................................................................................................ 44
2.1 Introduction .................................................................................................................................. 45
2.2 Methods ........................................................................................................................................ 48
2.2.1 Determining size, shape and orientation of cells to PEF ..................................................... 48
2.2.1.1 Calibration of images ......................................................................................................... 48
2.2.1.2 Determining size of the cell .............................................................................................. 49
2.2.1.3 Determining shape of a cell .............................................................................................. 49
2.2.1.4 Determining the angle of the cell with respect to the applied electric field .............. 49
2.2.1.5 Determining the density of cells in a given image ......................................................... 49
2.2.2 Statistical analyses ................................................................................................................... 50
2.3 Results ........................................................................................................................................... 50
2.4 Discussion ..................................................................................................................................... 54
Chapter 3: Nanosecond pulsed electric fields depolarize transmembrane poten-tial via
voltage-gated K+, Ca2+ and TRPM8 channels in U87 glioblastoma cells. (Based on published
manuscript) 57
3.1 Introductory Remarks ................................................................................................................. 58
3.2 Introduction ................................................................................................................................. 58
3.3 Materials and Methods ............................................................................................................... 61
3.3.1 Pharmacological manipulation of ion channel activity ................................................... 61
3.3.2 Calibration of PMPI voltage-dye ........................................................................................ 63
3.3.3 Statistical analyses................................................................................................................ 64
3.4 Results ........................................................................................................................................... 64
3.4.1 Calibration of PMPI .................................................................................................................. 64
3.4.1.1 Potassium calibration ........................................................................................................ 65
3.4.1.2 Calibration using electrophysiology ................................................................................ 66
3.4.2 Determining the threshold of electric field intensity required for nsPEF-induced
membrane depolarization. ................................................................................................................ 67
3.4.3 Fluorescence imaging of plasma membrane depolarization following a single 34 kV/cm
nsPEF. .................................................................................................................................................. 69
3.4.4 Inhibition of nsPEF depolarizing effect with BK channel blockers. .................................. 70
3.4.5 Depolarizing response of nsPEF is calcium-sensitive. ........................................................ 75
11
3.4.6 nsPEF-induced membrane depolarization is not mediated by voltage-gated Na+
channels; however, Na+ ions may still be involved. ....................................................................... 81
3.4.7 nsPEF-block is reversible. ....................................................................................................... 83
3.5 Discussion ..................................................................................................................................... 84
3.6. Conclusion ................................................................................................................................... 88
Chapter 4 - Plasma membrane depolarization and permeabilization due to electric
pulses in cell lines of different excitability ...................................................................................... 90
4.1 – Introductory remarks ............................................................................................................... 91
4.2 Introduction ................................................................................................................................. 92
4.3 Materials and Methods ............................................................................................................... 94
4.3.1 Cell culture and preparation ................................................................................................ 94
4.3.2 Potassium calibration of PMPI. .......................................................................................... 94
4.4 Results ........................................................................................................................................... 95
4.4.1 Cell Excitability ..................................................................................................................... 95
4.4.2 Plasma Membrane Permeability ........................................................................................ 99
4.5 Discussion ................................................................................................................................... 101
4.6 Conclusion .................................................................................................................................. 104
Supplementary Data ........................................................................................................................ 106
Chapter 5 – Discussion and Conclusion ...................................................................................... 108
5.1 Summary ..................................................................................................................................... 109
5.2 A comparative analysis of the theoretical and experimental interactions of PEF with cells
in vitro ............................................................................................................................................... 109
5.3 Nanosecond pulsed electric fields depolarize transmembrane potential via voltage-gated
K+, Ca2+ and TRPM8 channels in U87 glioblastoma cells .......................................................... 110
5.4 Plasma membrane depolarization and permeabilization due to electric pulses in cell lines
of different excitability .................................................................................................................... 112
5.5 Conclusion .................................................................................................................................. 113
5.6 Perspectives ................................................................................................................................ 115
References ......................................................................................................................................... 117
List of publications during Ph.D. candidature ............................................................................. 145
Journal articles ............................................................................................................................. 145
Presentations at International Conferences ............................................................................. 146
12
Table of figures
Figure 1.2 – Ion channels are classified by the stimulus which modulates their activity ........ 18
Figure 1.3 – The equivalent electric circuit model of the cell membrane. ................................. 19
Eq 1.1 Schwan equation (steady-state). ........................................................................................... 20
Figure 1.4 – The induced membrane potential varies along the cell membrane. ..................... 21
Figure 1.5 – Results from a case study of a patient with malignant melanoma. ....................... 26
Figure 1.6 – In-human trial for treatment of basal cell carcinoma with nsPEF. ....................... 27
Figures 1.7 (a-b) Photos of the electrodes, used for experiments presented in this thesis. ..... 31
Figure 1.8 – Fluorescence imaging setup. ...................................................................................... 32
Figure 1.9 – Direct comparison of YP and PI uptake following nsPEF exposure. .................... 33
Figure 1.10 – Fast-response vs slow-response voltage-probes. ................................................... 34
Table 1.1 – Describing fast vs slow voltage probes. ....................................................................... 35
Figure 2.1 – Schwan equation (steady - state). .............................................................................. 45
Equation 2.1 - Schwan equation (first - order). ............................................................................. 46
Figure 2.2 – Calcium wave entering the cell from the anodic pole following nsPEF. .............. 47
Figure 2.3 – Theoretical interaction of an electric field and a cell membrane. ......................... 48
Equation 2.2 - Determining the shape of a cell. ............................................................................. 49
Equation 2.3 – Equation describing relationship between cell shape and density with PEF-
induced membrane depolarization. ................................................................................................. 51
Figure 2.4 - Investigating pattern in baseline fluorescence. ........................................................ 52
Table 2.1 - Descriptive statistics for the two populations of cells grouped by baseline
fluorescence. ....................................................................................................................................... 53
Table 2.2 - Pearson correlation table from the multiple regression test divided into clusters.
.............................................................................................................................................................. 54
Table 3.1 - List of pharmacological agents used throughout this investigation. ....................... 63
Figure 3.1 - Calibration of PMPI by varying extracellular K+. ..................................................... 65
13
Equation 3.1 – Equation describing relationship between extracellular potassium
concentration and membrane depolarization. ............................................................................... 66
Equation 3.2 – Equation describing relationship between membrane potential and PMPI
fluorescence. ....................................................................................................................................... 66
Equation 3.3 – Goldmann equation. ............................................................................................... 67
Table 3.2 - Comparison between calibration methods for PMPI. ............................................... 67
Figure 3.2- Determining the electric field threshold for a single nsPEF to depolarize plasma
membrane. .......................................................................................................................................... 68
Figure 3.3 - Fluorescence imaging of U87 cells prior to and after delivering a single nsPEF
with an electric field intensity of 34 kV/cm. ................................................................................... 69
Figure 3.4- Effects of potassium channel blockers on nsPEF-induced membrane
depolarization. .................................................................................................................................... 71
Figure 3.5 - Concentration-dependent inhibition of nsPEF depolarization by TEA. ............... 72
Figure 3.6 - BK channel blockers significantly inhibit membrane depolarization following 34
kV/cm nsPEF. ..................................................................................................................................... 74
Figure 3.7 - Calcium-dependent threshold response curves in response to nsPEF of varying
electric field strengths. ...................................................................................................................... 76
Figure 3.8 - Comparing the role of calcium from intracellular, extracellular and endoplasmic
reticulum compartments. .................................................................................................................. 78
Figure 3.9 - Effects of calcium channel blockers on nsPEF-induced membrane
depolarization. .................................................................................................................................... 80
Figure 3.10 - Comparing effects from sodium and chloride channel blockers on nsPEF-
induced membrane depolarization. ................................................................................................. 82
Figure 3.11 - Reversibility of the TEA and Penitrem A inhibition of the nsPEF-induced
membrane depolarization. ................................................................................................................ 83
Figure 3.12 - Proposed mechanism of direct interaction between nsPEF and voltage-gated
channels along with downstream effects on non-voltage dependent channels. ....................... 86
14
Figure 4.1 - Phase-contrast images of all four cell lines used in experiments. .......................... 95
Figure 4.2 – Chemical depolarization of cells using K+. .............................................................. 96
Figure 4.3 – Representative depolarization dynamics following PEF exposure. ...................... 97
Figure 4.4 – Magnitude of depolarizing response to pulsed fields from 10 ns – 10 ms. .......... 97
Table 4.1 - The depolarization thresholds for all tested pulse durations and cell lines............ 98
Figure 4.5 - The strength-duration curve for depolarization thresholds of all cell lines. ........ 99
Figure 4.6 - Normalized permeabilization curve of all four cell lines to YO-PRO, 5 min after
the pulse application. ....................................................................................................................... 100
Figure 4.7 - Time dynamics of YO-PRO uptake and analyses. .................................................. 101
Table 4.2 - Parameters of the fitted symmetric sigmoid to the normalized data of YO-PRO
uptake. ............................................................................................................................................... 101
Table A1 - Statistical parameters for the strength-duration curve by cell line. ....................... 106
Table A2 - Additional statistical parameters from the strength-duration curve. .................... 107
15
Chapter 1:
General Introduction
16
1.1 Pulsed electric fields
The last few decades have seen an increased interest in the study of pulsed electric
fields, which has been particularly evident in medical and biotechnology sectors. They have
been shown to have broad applications in the food processing industry [1–3], for
cryopreservation of cell lines [4–6], enhancing gene or drug uptake by cells [7–10], and induce
cell death through necrotic or apoptotic pathways [11–13].
Understanding how electric fields influence cell behavior is important when
considering how to improve or expand current treatment options. The following section will
begin by taking a closer look at the cell and its intracellular contents, but more specifically at
the membranes that surround them, where electric fields are expected to interact.
1.2 Biological membranes
Understanding how a cell interacts with its environment begins with the very boundary
that separates them, which of course is its membrane. The cell membrane (Fig. 1.1) is
composed of a series of polar lipid molecules that have hydrophobic and hydrophilic regions
organized into a bilayer [14]. This structure displays self-organizing properties in an aqueous
environment that results in a boundary condition separating the cytoplasm from extracellular
fluids. A very similar arrangement of amphipathic lipid molecules within the cell serves to
separate organelles from the cytoplasm. These membranes are critical for selective transport
into and out of the cell.
In addition to the phospholipid bilayer, a host of other lipids, proteins and
carbohydrates can be identified. These molecules are highly variable in their distribution along
the membrane, each serving different functions ranging from signaling molecules to structural
support to name a couple. Transmembrane protein channels are of particular interest to our
topic and will be discussed in more detail.
17
Figure 1.1 – Structure of cell membrane. The cell membrane is a highly complex
structure whose fundamental unit is the phospholipid molecule (bottom right of the figure).
The amphipathic structure of this molecule results in the formation of a bilayer in aqueous
solution. Embedded within the membrane, multiple additional lipids, proteins and
carbohydrates serve to communicate with the external environment. Figure taken from:
https://www.thinglink.com/scene/634047922140348418.
1.3 Transmembrane proteins
Transmembrane proteins, to a large degree, dictate the function of the cell. Some serve
as signal conduits, whereby extracellular molecules interact with the protein leading to a
specific intracellular effect [15]. Others serve as selectivity filters responsible for modulating,
either passively or actively, the passage of ions. These ion channels are highly variable and are
critical for many cell processes.
Ion channels fluctuate between open and closed states, and these states can be
influenced through multiple mechanisms (Fig 1.2). Some examples include voltage-gated
channels, mechanically-gated channels, or ligand-gated channels. Upon activation, these
channels become permeable to specific ions. They can be highly specific, meaning they allow
just one type of ion to pass, or charge-specific allowing either cations or anions to pass.
18
Figure 1.2 – Ion channels are classified by the stimulus which modulates their
activity. Voltage-gated channels can be activated by fluctuations in a cells transmembrane
potential. Ligand-gated channels are activated through signal molecules that bind on extra- or
intracellular sites of the channel. Mechanically-gated channels are modulated through
changes in shape associated a physical stimulus. Image taken from Molecular biology of the
cell, 4th edition at https://www.ncbi.nlm.nih.gov/books/NBK26910/.
The selective nature of these ion channels is responsible for the generation of a
transmembrane potential, which is equally present and varies among intracellular organelles
as it is across the plasma membrane. The chemical basis of this voltage-gradient, known as the
resting membrane potential, is the uneven distribution of ions inside and outside of the cell
[16]. The electrical properties of ions, combined with the conductive properties of protein
channels and the insulating properties of the membranes lipid bilayer, have allowed the cell
to be modeled as an electric circuit. This has been useful when studying electrical
communication between cells for example, but also when developing treatment strategies to
modulate cell activity.
19
1.4 Describing the cell as an electrical circuit
In the 1950’s Alan Hodgkin and Andrew Huxley proposed a model to describe the ionic
mechanisms responsible for the propagation of electrical impulses along a giant squid axon.
As a general overview (Fig. 1.3), the Hodgkin-Huxley model represents the lipid bilayer as
parallel capacitors capable of storing charge and ion channels as variable resistors capable of
passing current. The transmembrane potential is generated across the cell membrane and
fluctuates according to the activity of the ion channels.
This model has been invaluable in understanding certain biological phenomena such
as electrochemical communication between cells, particularly between electrically excitable
cells in nervous and muscular tissues. Another application for this model extends into fields
interested in modulating cellular activity using applied electric fields.
Figure 1.3 – The equivalent electric circuit model of the cell membrane. In this
model, the lipid bilayer is represented as a pair of parallel capacitors and the transmembrane
ion channels are represented as variable resistors. Image adapted from Lehigh University
Bioengineers page, https://lehighbioe.wordpress.com/2012/10/23/the-cell-membrane-as-a-
circuit/.
20
1.5 Electric field interaction with the cell membrane
When cells are exposed to an electric field, an electric force is generated, which acts on
ions both inside the cell and in the external media. Because ions are charged molecules, this
force causes them to move along the electric field lines. Whereas the extra- and intracellular
solutions are conductive, the cells lipid membrane is non-conductive. As a result these ions
will accumulate along the membrane and generate a large transmembrane potential. At a
certain point, which is approximately 1 V [17, 18], the induced voltage exceeds the membrane
capacitance and breakdown of the membrane occurs. When considering the diameter of the
membrane is approximately 10 nm, the electric field strength associated with this threshold is
on the order of a MV/cm. This process, which is termed electroporation or
electropermeabilization is associated with enhanced membrane permeability.
To describe this effect, the Schwan equation (Eq. 1.1) was developed. This equation is
limited to modeling a spherical cell, and states that the induced membrane potential (Vm) is
proportional to the radius of the cell (R) and the applied electric field (E), and will not be
uniform along the cell membrane (Fig. 1.4). Extensions of this model have been developed to
help understand more complex models, such as irregular-shaped cells that can’t be accurately
described as spherical or ellipsoid.
𝑉𝑚 =3
2 𝐸𝑅 𝑐𝑜𝑠𝜃
Equation 1.1 Schwan equation (steady-state). This describes the effect of an applied
electric field (E) on the transmembrane potential (Vm) given a cell radius of (R) as a function
of the angle (θ).
21
Figure 1.4 – The induced membrane potential varies along the cell membrane.
This is an example of the Schwan equation applied to a spherical cell with a radius of 10 µm
and an applied field intensity of 44 kV/cm.
More recently, there has been a shift in methodology toward understanding the
biomolecular events occurring when an electric field interacts with a lipid bilayer. Molecular
dynamics (MD) simulations have helped to clarify some of the events associated with
electropermeabilization, and have allowed us to visualize the dynamics associated with
membrane breakdown [19–23]. Up to now, limitations in the computational power have
restricted MD to a period less than 1 millisecond following pulse delivery [24]; however, a
multitude of effects have been reported over much longer time periods. These effects appear
to be highly dependent on several factors such as; pulse duration, electric field strength,
number of pulses, and frequency of pulses delivered.
1.6 Factors influencing outcome following membrane exposure to an electric field
It is generally accepted that the initial step in membrane breakdown following PEF
exposure is the magnitude of the induced transmembrane potential [17, 18]. Thus, it is
unsurprising that electric field strength would play an important role in this process. Finding
-0.8
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22
the threshold for this response has been the subject of many investigations seeking to exploit
this consequence of PEF application. Achieving this threshold; however, is highly dependent
on the duration of the pulse delivered, such that eliciting a response using a shorter pulse
would require a stronger electric field than the same response using a longer pulse. For
example, using pulses ranging from 1 ns to 100 ms to stimulate gastrocnemius muscles, an
applied voltage of 4.5 kV was required for a 1.8 ns pulse to elicit a similar response to a 100
ms pulse delivered at 0.02 kV [25].
In addition to the electric field intensity and pulse duration, other important features
are; the number of pulses and the frequency at which they are delivered. These factors were
explored in [26], where nsPEF were investigated for their ability to cause swelling in Jurkat
cells. Single nsPEF were compared to 10 & 50 nsPEF. After 20 seconds significantly
enhanced swelling was seen as a function of number of pulses. In the same study, frequency
of pulses was explored, where swelling was measured after exposure to 10 pulses at 1 Hz or
10 pulses at 1 kHz. Similarly, significantly more swelling was observed in the group of cells
exposed to 10 nsPEF at 1 kHz when compared to the 1 Hz and the control groups.
In a study looking at Yo-Pro uptake in U87 cells following nsPEFs [27] the authors
report a significant enhancement in Yo-Pro uptake as a function of both number & frequency
of pulses delivered. Here, a single 10 nsPEF (1 p) was compared to 10 pulses (10 p) at 1 Hz,
10 Hz, and 100 Hz, and 100 pulses (100 p) at 1 Hz, 10 Hz, and 100 Hz. The results can be
summarized as follows: The greatest Yo-Pro uptake was observed – 100 p 100 Hz > 100 p 10
Hz > 100 p 1 Hz > 10 p 100 Hz > 10 p 10 Hz > 10 p 1 Hz > 1 p > control.
A noteworthy feature is evident when considering pulse shape in the context of the
literature presented above. In [28], using µsPEFs it was reported that the electric field
intensity required to permeabilize 50 % of the cells was reduced by 20 % when the authors
used symmetrical bipolar pulses. The working hypotheses for these results propose that i)
the polar asymmetry following a unipolar pulse is counterbalanced when a bipolar pulse is
delivered and ii) bipolar pulses increase the odds that a non-spherical cell are permeabilized.
23
In contrast to this research, several articles show a dampened effect when bipolar
nanosecond pulses are used. In [29], the addition of a second phase (of opposite polarity)
cancelled the effect of the initial monopolar phase in both intracellular calcium mobilization
and cell survival. These results persisted in spite of a doubling of total energy delivered to
cells, and was not dependent on pulse duration (60 ns or 300 ns), amplitude (15 – 60
kV/cm) or number of pulses delivered (1 – 60). This dampening effect gradually decreased as
the delay between the bipolar pulses increased. A similar dampening effect was observed for
calcium uptake [30] as well as measures of plasma membrane integrity Calcium Green-1,
Propidium Iodide and FM1-43 [31] when comparing bipolar effects to monopolar effects.
Although some explanations were put forth to explain the differences between µs and
ns bipolar pulses, the duration of the pulse is critical and is based on a biological constant
known as the membrane charging constant, which will be discussed in further detail in the
next section.
1.6 The role of pulse duration in PEF effects
Recall that the induced transmembrane potential is due to the accumulation of ions
along the cells membrane. This process obviously requires time, and is referred to as the
charging time, or charging constant. Although it varies slightly between cells, the charging
time is on the order of a few hundred nanoseconds [32–34]. Pulse durations that are longer
than the charging constant will have very different effects those that are shorter.
The following sections will examine the different effects expected when using pulsed
electric fields of various durations. For simplicity, pulses that are longer than the charging
time will be referred to as pulsed electric fields (or PEF), and those that are shorter will be
referred to as nanosecond pulsed electric fields (or nsPEF).
24
1.7 PEF effects and applications
At longer durations, in the micro- or millisecond range, PEF have been shown to be
effective at delivering drugs, proteins, and DNA across the cell membrane [35–41]. By
adjusting the number, frequency and intensity of the pulses one can reversibly or irreversibly
permeabilize the plasma membrane.
1.7.1 Irreversible electropermeabilization (IRE)
Irreversible electropermeabilization (IRE) has been studied as a purely electrical
treatment for tumors [13, 42–45]. Here, the cell is unable to repair the damage imposed by the
electric field. A review of this technique [46] looked at results from 106 patients over a period
ranging from 3 – 18 months. Efficacy of treatment ranged from 67 – 100% over this period.
Most recently, another human trial has shown promising results [47]. In this study, 30
patients were treated with liver tumors. They were monitored for 6 months following
treatment where treatment success was defined as no evidence of residual tumors in the
ablated area from CT and ultrasound scans. After 3 and 6 months, success was achieved in
79% and 66% of the patients, respectively.
1.7.2 Reversible electropermeabilization
Contrary to IRE, reversible electropermeabilization utilizes the ability of the
membrane to repair itself as an advantage. Of the two, reversible electropermeabilization has
been most thoroughly investigated, and offers a greater number of potential therapies. Gene
electrotransfer (GET) is one such application, where DNA is introduced into the cell and makes
it possible to regulate the production of a desired transgene. A very thorough review [39]
highlights the vast number of disorders that can potentially be treated, including Parkinson’s
disease, HIV/AIDS and cancer to name a few.
A more recent review of clinical GET trials highly the broad potential for this therapy
[48]. In this review, the author summarizes the results of more than 50 clinical trials (some of
which are ongoing) where GET has proven to be a safe and effective method to treat various
25
cancers by stimulating immune activity or disrupting angiogenesis in tumors; as well as a role
in DNA vaccines for HIV, Hepatitis, Human papilloma virus, and Hantaviruses.
Electrochemotherapy (ECT) is another application for reversible
electropermeabilization, where chemotherapeutics (or high concentrations of calcium) can be
injected systemically or locally followed by electropulsation of the tumor. Here drugs such as
bleomycin and cisplatin have been selected for their combination of low membrane
permeability and high cytotoxicity, and when combined with electropulsation, the toxicity of
these agents has been significantly enhanced [49–51].
Recently, a case study looked at the effects of calcium electroporation and
electrochemotherapy on a patient with malignant melanoma [52]. This patient had numerous
metastases (Fig. 1.5) yet 12 months following treatment complete leveling was observed in
both treated and non-treated lesions. The fact that non-treated tumors responded highlights
the potential role of the immune system in mediating this response. Biopsies taken upon
completion of the follow-up period revealed an absence of malignant cells.
1.8 nsPEF effects and applications
When pulse durations shorter than the charging constant are applied, the plasma
membrane no longer shields the intracellular environment [32, 33], and very different effects
can be expected. Effects such as mitochondrial depolarization [53, 54], caspase activation [55,
56] and nuclear condensation [57, 58]; all effects typical of cell death by apoptosis, have been
reported. Additional effects such as cytoskeleton disruptions, including microtubule [27] and
actin [59] assembly have also been reported.
26
Figure 1.5 – Results from a case study of a patient with malignant melanoma. The
top two images were taken prior to treatment using electrochemotherapy and calcium
electroporation. In these images multiple cutaneous metastases are evident. The bottom two
images were taken 16 months following treatment. A complete leveling was observed in both
treated and non-treated metastases. Biopsies of the pigmented lesions were found to be non-
malignant. Results and images from [52]
Whereas intracellular effects are specific to nsPEF, there is a lot of evidence suggesting
additional effects occur on the plasma membrane. For example, membrane permeability was
found to be enhanced following nsPEF exposure, where YO-PRO [27] and bleomycin [60]
uptake into the cell was observed. In an experiment using giant unilamellar vesicles, a single
nsPEF resulted in the delivery of siRNA molecules into the cytoplasm [61].
27
It has been hypothesized that these ultra-short fields may exert effects directly on
transmembrane protein channels in the plasma membrane [62]. Experimental evidence exists
that supports this, where nanosecond pulses have resulted in direct activation of voltage-gated
channels [63–65].
While nsPEF have demonstrated very unique effects compared to PEF, there is still a
need for clinical data to validate the translation of these effects in human trials. The first
human trial using nsPEF for cancer treatment was published in 2014 [66]. In this study a total
of 10 tumors were treated with nsPEF on 3 patients with basal cell carcinoma. Of the tumors
treated, seven were completely free of cancerous cells, two had partially regressed, and one
recurred 10 weeks after treatment. An example of tumor treatment in this study can be seen
in Fig. 1.6 below.
Figure 1.6 – In-human trial for treatment of basal cell carcinoma with nsPEF. An
example from [66], where the first human trial was conducted testing nsPEF efficacy on skin
cancer. Three patients were treated using nsPEF and followed for several weeks following
treatment. Images above are a representative example of the effects observed. The first and
second images were taken pre- and immediately post-nsPEF exposure. The final image was
taken 10 weeks post-treatment where there was no evidence of tumor recurrence. This was
confirmed by histological analysis of biopsy.
Despite all of the promising research using PEF and nsPEF, this field is still continuing
to evolve. Many questions still remain with respect to the mechanism of action of PEF/nsPEF
28
effects on biological systems. Understanding these mechanisms will help us overcome some
of the limitations present in this field of study.
1.9 Limitations of PEF/nsPEF as a clinical treatment
The major limitations facing experimentation using pulsed electric fields (PEF/nsPEF)
for treating humans are time and money. An abundance of research demonstrates the
potential of electrically based therapies. Recently, the handbook of electroporation was
published [67] containing a comprehensive series of chapters from various contributing
authors highlighting studies from modeling and simulations to in vitro work right up to
clinical applications. Despite the amount of research, very few countries offer treatments using
pulsed electric fields.
As a result, patients who could benefit from these treatments aren’t even being given
the option. And those who may be aware will have to make the choice between paying from
their own pockets and choosing those treatment options that are covered by health insurance
policies. That is why I say time and money are the major limitations. More money is required
to generate further research, and this takes time. With that said, it is an honor contribute in
the most humble way to this ever-growing field hoping that I can add to the current body of
knowledge.
The pulse generators, as well as the fluorescent indicators of transmembrane potential
and membrane permeability, used for these experiments will be discussed in detail in the
following section.
1.10 General methods
The following section will provide a detailed overview of some of the techniques and
equipment used throughout the work presented in this thesis. Attention will be given to
explaining the cell lines used and how they were maintained; the different pulse generators
and electrodes used; the fluorescence microscopes used and which fluorescent indicators were
selected; the methods involved in extraction of data from images, and the statistical
29
methodology applied. Part of the work described in this thesis was the result of a collaboration
with the University of Ljubljana. My contribution to this collaboration involved data collection
and statistical analyses. Whereas we investigated the role of pulse durations ranging from 10
ns to 10 ms, the majority of the work presented in this thesis focuses on 10 nsPEF, which is
the primary focus of our lab.
1.11 Culture and maintenance of cell lines
1.11.1 Cell lines and maintenance
Three cell lines were used for the experiments that will be presented. Chinese hamster
ovary (CHO) cells (European Collection of Authenticated Cell Cultures ECACC, cells CHO-K1,
cat. no. 85051005, obtained directly from the repository), U87-MG human glioblastoma cells
(ECACC, Public Health England, cat. no. 89081402) and HT22 immortalized mouse
hippocampal neurons (The Salk Institute, La Jolla, CA) were grown in an incubator at 37 °C
at 5 % CO2 for 2-5 days before experiments. HT22 cells were used in their non-differentiated
and differentiated states. The procedure used to differentiate these cells will be explained
further in section 1.11.2
Experiments were completed in laboratories in Limoges, France and Ljubljana,
Slovenia. In Limoges, depending on the experimental setup, cells were grown in one of two
ways. They were either grown on Poly-Lysine (Sigma-Aldrich, Germany) coated 22 mm glass
coverslips in 35 mm Petri dishes (VWR International, USA); or they were grown in 35 mm
glass FluoroDishes (World precision instruments, USA). In the former condition, the 22 mm
glass coverslip was transferred into a customized plastic ring which could be mounted onto
the microscope. In Ljubljana, cells were grown in 40 mm Petri dishes (TPP, Austria). To ensure
these subtle differences in methodology were not significantly influencing the results,
experimental results were compared between labs.
For growth and maintenance of cell lines, CHO cells were grown in Ham-F12 media
(Sigma-Aldrich, Germany), U87 cells in MEM (Sigma-Aldrich, Germany) and the HT22 cells
30
in DMEM (Sigma-Aldrich, Germany) growth medium. All growth media were supplemented
with 10% fetal bovine serum (Gibco, France or Sigma-Aldrich, Germany, cat. no. F9665), L-
glutamine (StemCell, Canada) and antibiotics.
1.11.2 Differentiation of HT22 cells
HT22 cells were used in their non-differentiated and terminally differentiated forms.
In order for HT22 cells to be differentiated, DMEM growth media had to be replaced with
Neurobasal media (Thermofisher, USA, cat. no. 21103-049), and supplemented with 0.5 mM
L-glutamine and 1 mL B-27 (Thermofisher, USA, cat. no. 17504-044) for every 50 mL
Neurobasal media. Cells were maintained in this differentiation medium for 24 – 48 hours
prior to experimentation.
1.12 Exposure of cells to electric pulses
Cells were exposed to different pulse durations (10 ns, 550 ns, 1 µs, 10 µs, 100 µs, 1 ms,
and 10 ms). To accommodate experiments using these pulse durations, three different pulse
generators were used. For 10 ns pulses, a commercially available nsPEF generator (FPG 10-
1NM-T, FID Technology, Germany) with 50 Ω output impedance was used. The 10 ns pulse
durations (13.6 ns full width at half magnitude (FWHM) duration and a 5.2 ns rise time) were
applied with electric field intensities ranging from 16.5 – 52.0 kV/cm. A high-voltage
measurement device (tap-off) connected to a digital phosphor oscilloscope (DPO 4104,
Tektronix, USA) was used to visualize the time-domain measurements of each pulse. Pulses
were delivered to cells by positioning the electrodes (Fig. 1.7 a), comprised of two stainless-
steel electrodes (1.2 mm gap) with a 50 Ω impedance resistive load in parallel, using a
micromanipulator (MP28, Sutter Instruments USA). The applied electric field was
numerically determined [27]. Numerical modelling of the electrode delivery system was
performed with a Finite-Difference Time-Domain (FDTD) based electromagnetic solver, and
a finest spatial mesh of 100 μm.
31
For pulse exposures of 550 ns and 1 µs, a laboratory prototype nanosecond generator
with H-bridge MOSFET amplifier architecture and additional peripheral circuitry for voltage
adjustments and safety was used. Voltage could reach 1 kV with an accuracy of 3 %. For pulse
exposures of 10 µs – 10 ms a commercially available BetaTech electroporator (Electro cell B10,
Betatech, France) was used, and the current was measured with either current probe CP030
(Teledyne LeCroy, USA) or a Pearson current monitor (Model 2877, Pearson Electronics Inc.,
USA). Pulses longer than 10 ns were applied using either stainless-steel wire electrodes with a
4 mm intra-electrode distance and 1.29 mm diameter (16 gauge needle) or Pt/Ir wire
electrodes with 5 mm intra-electrode distance and 0.75 mm diameter (Fig. 1.7 b). The
numerical calculations show that the electric field in the middle of the electrodes is
approximately homogeneous [68]. To compare the results obtained with both electrodes, we
approximated the electric field between the electrodes as E = U / d, where U is the applied
voltage and d the distance between the electrodes. We adapted the applied voltage to achieve
the same electric field and acquired images in the middle of the two electrodes.
Figures 1.7 (a-b) Photos of the electrodes, used for experiments. A - Electrodes used
for delivering 10 ns pulses; B - electrodes used for delivering pulses longer than 500 ns.
Respective traces for 10-ns and 1-µs pulses delivered are to the right of electrode images, along
with a numerical simulation of the nsPEF field distribution.
32
1.13 Fluorescence imaging
Experiments conducted in Limoges were performed on a DMI6000 confocal
microscope (Leica Microsystems, Germany) using a 63x oil immersion objective (for
experiments measuring membrane potential) or a 20x objective (for experiments measuring
membrane permeability). A Spectra 7 light engine (Lumencor, USA) was used for fluorescence
excitation, whereas the emitted light was captured with an electron-multiplying charge-
coupled device camera (EMCCD Evolve 512, Rope, USA). Fig. 1.8 shows the imaging setup.
Figure 1.8 – Fluorescence imaging setup. An image of the workstation where the nsPEF
experiments were performed.
In Ljubljana, an inverted microscope AxioVert 200 (Zeiss, Germany) was used for
experiments with a 20x (when measuring membrane permeability) or 40x (when measuring
membrane potential) objective. Samples were excited using a high-speed polychromator
(Visitron systems GmbH, Germany), and the emitted fluorescence was acquired with a
VisiCam 1280 CCD camera (Visitron, Germany).
33
1.14 Fluorescent indicators for measuring transmembrane potential and membrane permeability
1.14.1 Measuring membrane permeability
Selecting a fluorescent dye for measuring membrane permeability was straightforward
because there are only a few that are commonly used in the literature. Generally, membrane
integrity is measured using either propidium iodide (PI) or YO-PRO (YP). There are multiple
studies using these dyes; however, when directly compared [69], YP was found to be a more
sensitive measure for membrane permeability than PI (Fig. 1.9). This difference was attributed
to the size of the molecule, insofar as YO-PRO has much less steric hindrance associated with
its planar configuration. For that reason it was used for the permeability experiments
presented in this thesis. In all cases, it was used at a concentration of 1 µM.
Figure 1.9 – Direct comparison of YP and PI uptake following nsPEF exposure.
These results demonstrate the difference in sensitivities between YP and PI for measurement
of membrane integrity. Image taken from [69].
34
1.14.2 Measuring transmembrane potential
Selecting a voltage probe, on the other hand, required more consideration. Typically
voltage-sensors are divided into two slow- or fast-probes. Depending on cell type (excitable vs
non-excitable) or on the experimental objectives, both voltage-sensors have advantages and
disadvantages. A summary of their differences is available below in Table 1.1.
The major difference between slow and fast probes is the mechanism by which they
permit the measurement of Vm. (Fig. 1.10). Slow probes, also called Nernstian probes, undergo
Vm - dependent changes in their transmembrane distribution. These probes typically are
considered when looking for long-term changes (seconds to minutes) in membrane potential
that is due to alterations in ionic permeability of the membrane.
Figure 1.10 – Fast-response vs slow-response voltage-probes. A In response to a
change in the local electric field, fast-response probes undergo a change in the electronic
configuration. This structural change leads to changes in the fluorescent properties of the
molecule. B Slow-response probes undergo a transmembrane redistribution that is dependent
on the membrane potential. Source for the figure -
https://www.thermofisher.com/fr/fr/home/references/molecular-probes-the-
handbook/probes-for-membrane-potential/introduction-to-potentiometric-probes.html
35
Whereas the optical response time for slow probes prevents the study of single action
potentials in excitable cells such as neurons and muscle cells, the magnitude of response is
much greater than fast-response probes, in some cases approaching 100 x more sensitive (~
1% change per mV). This allows for the measurement of subtler changes in Vm over time.
Fast-probes, or electrochromic probes, are typically selected when the interest is in
very rapid changes in membrane potential. These probes undergo a change in the electronic
structure of the molecule when the surrounding electric field is changed. This change in
structure results in a change in fluorescent properties. Because the change in fluorescence does
not depend on translocation across the membrane, the optical response time is extremely fast.
Contrary to the slow probes, the cost of the rapid response is a significant reduction in
sensitivity (~ 2 – 10% change per 100 mV).
Slow Fast
How they work Membrane potential-dependent change in their transmembrane distribution results in change in fluorescence
A change in surrounding electric field results in a change in the electronic structure of the probe which changes the fluorescent properties of the molecule
Magnitude of change ~ 1% change per mV ~ 2-10% change per 100 mV
Optical response Suitable for detection of average membrane potential changes (from respiratory activity, ion-channel permeability, drug binding etc.)
Suitable for detection of transient, rapid changes in potential (ms) in neurons and cardiac cells
Examples Carbocyanines and rhodamines (cations); and oxonols (anions)
AminoNaphthylEthenylPyridium (ANEP) dyes; Förster resonance energy transfer (FRET) sensors; FluoVolt*
Table 1.1 – Describing fast vs slow voltage probes. Comparing the pros and cons of
various types of probe based on their mechanism of action, magnitude of change and optical
response. * FluoVolt has magnitude of change closer to 25% per 100mV.
36
A commercially available slow probe, known as plasma membrane potential indicator
(PMPI); a commercially available fast-probe, FluoVolt; and a genetically encoded fast probe,
ArcLight were tested and compared to determine how they responded to a single nsPEF.
Experiments were performed to determine which would be more appropriate for our
experiments.
ArcLight is part of the rapidly evolving family of genetically encoded voltage sensors.
This next generation technology is made possible due to a fusion of a voltage sensor found in
the sea squirt, Ciona intestinalis, with a fluorescent protein (GFP) found in the jelly fish,
Aequorea victoria [70]. DNA transfection into the host cell and subsequent expression is made
possible using a baculovirus which is unable to replicate in mammalian cells [71–73]. First
described in 2012, ArcLight has been considered a revolutionary step forward in fast-response
probes and genetically encoded voltage sensors in particular because of its relatively large
magnitude of response, which has been reported to approach 35% per 100 mV change in
transmembrane potential [70].
Despite this large magnitude of response when compared to other fast voltage-probes,
when ArcLight-transfected U87 cells were exposed to a 34 kV/cm nsPEF, the relative change
was quite minimal. With such a minimal response taken with the relative inconvenience
associated with the time taken to transfect the cells, this probe was not considered ideal for
the purpose of our intended experiments.
The second fast-response voltage-sensing probe, FluoVolt, is considered to be the next
generation for electrochromes not included in the genetically encoded family. Because of the
commercial nature of this voltage-sensitive dye, the chemical structure is unknown.
Lifetechnologies, the company who distributes this dye, states that its optical resolution is in
the sub millisecond timescale and exhibits a magnitude of response up to 25% per 100 mV
change in membrane potential.
Although easy to use, requiring a simple mixing procedure along with a 15 – 30 minute
incubation period, the response observed following a 34 kV/cm nsPEF was similar to that
37
achieved with ArcLight. A recent article [65] using nanosecond pulsed electric fields confirmed
that the resultant response of FluoVolt, in this case to a 3 kV/cm, 200 ns PEF was closer to 5%
than the 25 % expected. This level of response would not be adequate to determine potentially
subtle effects following application of various ion channel modulators.
The commercially available slow-response probe, PMPI, was determined to be the
most capable for answering the questions we set out to answer, and will be addressed in the
following section. This probe, also of unknown chemical structure because of its commercial
nature, was able to reliably respond with a magnitude around 20 - 30x greater than the other
probes tested. Because of the kinetics of this dye, such that an increase in fluorescence is
associated with a depolarization of the transmembrane potential, the chemical family could be
determined.
Three types of slow-response probes exist: Carbocyanines, rhodamines, and oxonols.
The two former families are cationic species. Because they are positively charged, these
molecules tend to be used more for monitoring mitochondrial membrane potential whose
resting potential is significantly more negative than that of the cell’s plasma membrane [74,
75]. Oxonol dyes, on the other hand, are anionic species which do not label mitochondria or
other intracellular organelles. This is the choice family of dyes for monitoring changes in
plasma membrane potential in vitro [76].
When compared with ArcLight and FluoVolt, PMPI has the advantage of a significantly
greater sensitivity to our nsPEF conditions. Moreover, it requires a simple dilution (0.5 µL/
mL) into the imaging solution and a 30 minute incubation period prior to use. Finally, PMPI
has been relatively well tested and validated as an appropriate tool for the optical
measurement of transmembrane potential, even when compared to patch-clamp
electrophysiology [77–80]. Taken together, this voltage-sensitive dye was selected to
investigate nsPEF effects on Vm in the experiments to be presented.
38
1.15 Image acquisition
Images were acquired using MetaFluor software (Molecular Devices, USA) in Limoges
and with MetaMorph software (Molecular Devices, USA) in Ljubljana. Prior to
experimentation the growth media was replaced with Live cell imaging solution (Molecular
probes-A14291DJ) with the addition of 20 % D - glucose at a concentration of 1.0 mg/mL.
Images were acquired every 30 seconds for experiments using PMPI, and every 3 seconds for
those using YO-PRO. Where electropulsation occurred, a 5 minute baseline of fluorescence
was collected for PMPI experiments, and a 30 second baseline for YO-PRO experiments.
Figure 1.11 – Example of image processing and data extraction. The ROI’s are traced
around the perimeter of each cell membrane in the brightfield image (top left). These ROI’s
are then copied and pasted into the fluorescence image series (top right). Both the raw
fluorescence data (bottom left) and relative fluorescence data (bottom right) is extracted for
statistical analyses.
0
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30
40
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39
An example of image analysis using HT22 undifferentiated cells in Image Analyst MKII
software (Fig. 1.11). The initial step involves tracing the perimeter of the visible region of each
cell membrane which will be the regions of interest (ROIs) when extracting data. Following
this step, the ROIs were copied from the bright field image and then pasted into the
fluorescence image series. An additional ROI is traced in an area of the fluorescence image
series where no movement is observed. This final ROI will serve to remove the background
noise by subtracting its value from the entire image series. Finally, the raw and relative (ΔF/Fo)
data is extracted and exported for statistical analysis. This was an example where PMPI was
used. YO-PRO experiments were handled in the same manner.
1.16 Statistical analysis
Following image analysis and extraction of data, statistical analyses were performed
using IBM SPSS 19 or SigmaPlot v.11. Multiple types of statistical tests were performed
throughout this thesis, all of which were parametric tests. Therefore, certain assumptions
pertaining to the dataset had to be met for these tests to be properly used and interpreted. The
following assumptions are required for all tests used in this thesis. Additional assumptions are
required depending on the statistical test used. For a review on the more specific assumptions,
refer to [81].
1.16.1 Independence of data
Because the experimental questions looked at differences between groups, the
assumption of independence had to be met. This assumption simply states that the
observations were collected on different subjects. This can be slightly difficult in in vitro
studies since we are often comparing different effects on the same cell line. Therefore, to
ensure the design was as balanced as possible, data was collected and repeated on different
days ensuring that the assumption of independence was met.
40
1.16.2 Normal distribution
Since parametric tests are based off the normal distribution, it is important to ensure
that the data collected within groups is normally distributed. To measure normality, several
measures should be evaluated; including plotting the frequency distribution, evaluating the
shape of the data using values of kurtosis and skewness, analyzing P-P plots to determine if
the data collected was comparable to a theoretical normal distribution, and using the
Kolmogorov-Smirnov (K-S) test which compares the data with a theoretical dataset containing
the same mean and standard deviation.
1.16.3 Homogeneity of variance
The final general assumption to be met involved variability in the dependent variable.
This requires that the variances within conditions are approximately similar. As an example,
suppose we are interested in the electric field threshold for a 10 ns PEF. To meet this
assumption, the variability should be similar for each electric field intensity used. Levene’s test
is used for this purpose, where a significant result suggests that the variance between
conditions is not similar.
1.16.4 Violations of statistical assumptions
Two options are available when the data does not meet the conditions for parametric
testing: Either the data can be transformed using one of many available options, or it can be
removed from the analysis. The drawback to transforming data is that one must also change
any conclusions. For example, if we log transform our data for membrane depolarization, any
conclusions must interpreted in the same way. For the purpose of our results, it seems
unhelpful to make claims about the effects of PEF on the log transformed membrane
depolarization.
Therefore, we are left with the alternative, which is to remove any cases that are
significantly influencing the dataset. For the purpose of analyses outliers were defined as cells
(ROIs) whose fluorescence was beyond 2 standard deviations from the group mean (+/- 2 SD).
41
1.16.5 Additional inclusionary criteria
It is worth noting that prior to testing the assumptions, additional criteria was
necessary for inclusion. In order to be considered for analysis, the cells being measured could
not undergo any excessive movement. This included an automatic exclusion of any cells
entering or exiting the field of view after the experiment commenced. Moreover, cells were
excluded in the event that other debris entered the image series and altered the measured
fluorescence in those ROIs. Finally, a stable baseline was required prior to any experimental
manipulation in order for data from that cell to be further considered.
1.16.6 Definition of threshold
Many of the results to be presented will refer to a threshold. Whether it refers to PMPI
experiments or YO-PRO experiments, the threshold was defined as the minimum electric field
intensity required to produce a response that was significantly different than the control as
determined by the statistical test performed. In the case of PMPI experiments, the threshold
refers to membrane depolarization, whereas in YO-PRO experiments this refers to membrane
permeability. The alpha criteria was set at α = 0.05 for all tests.
1.16.7 Statistical terminology and abbreviations
Each statistical test is associated with an abbreviation. Using an ANOVA, the following
will help elucidate some of the terminology that will be encountered when reading this text.
The first letter, F, is used to represent the ANOVA. If a t-test is used, a t will replace the F; and
in the case of a discriminant analysis, a Λ will take its place. In brackets, 2 numbers are seen
and these represent the degrees of freedom (between, within groups). Between groups degrees
of freedom (df) are calculated by subtracting 1 from the total number of groups tested. This
would indicate that 3 groups were tested in the example below. Within groups df relates more
to the sample size, where the number of groups is subtracted from the total sample size.
Following the same example, this would indicate that the total sample size was 30. The number
42
14.20 is the obtained F-value, which is compared to a critical F-value and is dependent on the
degrees of freedom and the threshold for statistical significance.
F (2, 27) = 14.20, p<0.01, Ω2 = 0.80
The p-value is a measure of statistical significance. If the F-value obtained is greater
than the critical F-value, the p-value will represent a statistically significant difference between
the groups tested. This value is traditionally set to either 0.05 or 0.01, which suggests that
there is a 5 % or 1 % probability that the measured significance is false. The final number is
the effect size Ω2. This value represents the proportion of change in your dependent variable
due to the experimental manipulations of the independent variable. The value 0.80 means
that 80 percent of the variability in your dependent variable is due to the experimental
manipulation. Additional abbreviations will be encountered for parameters such as; sample
size (n), average (X), and standard error (SE).
1.17 Objectives and hypotheses for this Thesis
As a general overview of this chapter, whether the cell or the intracellular organelles
are targeted, ultimately the membranes surrounding them are influenced using pulsed electric
fields. Depending on the desired effect, pulse durations can be used which are greater than or
less than the membrane charging constant. When pulse durations are greater than the
charging time, we observe effects at the level of the plasma membrane. Conversely, shorter
pulse durations have the ability to penetrate the plasma membrane and influence intracellular
organelles.
The research presented in this thesis investigated pulse durations ranging from 10
nanoseconds up to 10 milliseconds on several cell lines. The major point of interest will be to
study the potential for these fields to act on transmembrane proteins, specifically ion channels.
Three experimental chapters will be presented. Because our lab specializes in nsPEF exposure,
the bulk of the data will be centered on these effects. The longer pulse durations were used in
43
the final experimental chapter, which was a collaborative venture between our lab and the
University of Ljubljana.
The first chapter presents a statistical perspective on the results of nsPEF-induced
membrane depolarization. Here we examined experiments on 500 cells over 3 years and
attempted to use factors common in electrophysical models, such as cell size, shape,
orientation to the electric field, and density of cells exposed to determine how well these
parameters could predict the observed depolarization response.
The second chapter investigates the potential for nsPEF to modulate ion channel
activity in U87 cells. Here, a vast number of broad and specific modulators of a variety of ion
channels were used to determine whether they could influence the depolarizing response
following electric field exposure. The null hypothesis being, if the depolarizing response to
these fields was predominately due to electroporation of the plasma membrane, blocking
individual ion channels should not significantly alter the effect.
Finally, knowledge gained from these chapters was applied to several cell lines in a
collaborative project with the University of Ljubljana. Both excitable and non-excitable cell
lines were selected to determine effects of pulse durations ranging from 10 ns to 10 ms on
membrane depolarization. Membrane permeability was an additional parameter explored for
these experiments. The goal for this chapter was to determine whether an electric field
intensity could be found that was able to permeabilize the cells without significantly altering
the transmembrane potential. The application of such a pulse would be to permeabilize cells
targeted during electrochemotherapy treatment, while minimizing pain associated with
electrically exciting surrounding nervous tissue. A manuscript has been submitted for this
collaboration and is currently under review. The results presented in this thesis will include
only those that I directly contributed to.
44
Chapter 2:
A comparative analysis of the
theoretical and experimental
interactions of PEF with cells in vitro
45
2.1 Introduction
Despite decades of research into the effects of PEF on biological systems, the
mechanisms by which electric fields interact with cells are not fully understood. The present
consensus relies on the combination of mathematical models and computer simulation to
describe and predict experimental data.
A pioneer in this field of research, H. P. Schwan, was the first to mathematically
describe the interactions between electric fields and biological systems in the late 1950’s [82].
This relationship is summarized in Fig. 2.1 below, where the induced transmembrane
potential, (Vm), is expected to be proportional to the applied electric field (E) and the cell radius
(R). The cosine function predicts that Vm will be non-uniformly affected along the cell
membrane, such that the greatest effects would be predicted at areas of the membrane
adjacent to the electrodes. Moreover, it suggests that when two cells are exposed to an electric
field of equal intensity, the greatest effects on Vm will be observed in the larger cell.
𝑉𝑚 =3
2 𝐸𝑅 𝑐𝑜𝑠𝜃
Figure 2.1 – Schwan equation (steady - state). This steady-state equation predicts the
induced transmembrane potential (Vm) on a cell with a radius (R) following the application of
an electric field with an intensity (E). The cosine function (θ) suggests the effect will be
influenced by the angle at which it interacts with the membrane.
An important issue to consider with the steady-state Schwan equation is that it does
not consider the time required to superimpose an external electric field on the cell’s resting
membrane potential. This has become especially important as pulse durations have become
46
shorter than the time constant for charging the plasma membrane. For that to be considered,
a modification of Schwan’s equation incorporates the pulse duration (t) and the membrane
charging time (τm) (Eq 2.1).
𝑉𝑚 =3
2 𝐸𝑅 𝑐𝑜𝑠𝜃 (1 − 𝑒
(−𝑡𝜏𝑚
))
Equation 2.1 - Schwan equation (first - order). Extension of the Schwan equation that
incorporates time (t), and the membrane charging constant (τm).
One limitation with the Schwan equation is that the more a cell deviates from a
spherical shape, the less it becomes applicable. With that said, regardless of the shape of the
cell, experimental data has demonstrated repeatedly when fluorescent markers with high
temporal resolution are used, the greatest effects are observed at membrane regions adjacent
to the electrodes [83–86].
An excellent example of this was published recently, when a genetically encoded
calcium indicator, GCamP, was used in experiments using nsPEF [87]. In Fig. 2.2 the authors
delivered 100 x 10 ns pulses at either 10 Hz (top series) or 1 Hz (bottom series) with an electric
field intensity of 44 kV/cm. In both conditions, although the time dynamics differ, a wave of
calcium can be seen entering the cell moving along the electric field gradient from the anode
to the cathode.
Sometimes, however, we find unanticipated results in the literature. Theory would
predict [88] that, under the same conditions, the cell with a larger radius should be more
influenced by the electric field than the smaller one. Yet we find results that show a positive
relationship [88], an inverse [89], or no relationship [90, 91] between the size of a cell and the
observed effects.
47
Figure 2.2 – Calcium wave entering the cell from the anodic pole following
nsPEF. The top series shows results following 100 x 10 nsPEF, delivered at 100 Hz and an
electric field intensity of 44 kV/cm. The bottom exposed cells to the same parameters except
the pulses were delivered at 1 Hz. The numbers above the images are measure of time in
seconds. Figure adapted from [87].
It is possible that there are some methodological differences that could shed some light
on this discrepancy. For example, there were different cell types used in those experiments,
which included yeast, rodent and human cell lines. All cells exhibit fairly characteristic growth
patterns and rates, specific to their cell type. Since the density of cells being exposed is
expected to play a significant role in the observed effect [86, 92], perhaps this factor could
have contributed to the variation in results when considering the size of the cell. Despite the
models describing the influence of cell density on PEF effects, I was unable to find any
published articles that attempted to experimentally account for this parameter.
The objective for this section will be to determine how factors such as cell size, shape,
orientation and density can predict membrane depolarization in U87 cells exposed to a single
10 ns PEF. Although analytical and numerical models for these parameters have been
described [85, 86, 92], (Fig. 2.3) there have been no studies which have tried to experimentally
determine how all of these factors simultaneously influenced the induced transmembrane
48
potential. For these analyses, additional factors such as temperature, medium conductivity,
electric field intensity, pulse shape and duration have all been held constant to reduce as many
extraneous variables as possible. One would expect that a significant contribution to the
induced transmembrane potential following a PEF will be accounted for by variables such as;
cell size, shape, the angle at which the PEF interacts with the cells major axis, and the density
of cells in the field of view.
Figure 2.3 – Theoretical interaction of an electric field and a cell membrane.
Factors such as cell size (top left), shape (top right), orientation to the electric field (bottom
left), and density of cells (bottom right) will influence the observed response following PEF.
2.2 Methods
2.2.1 Determining size, shape and orientation of cells to PEF
2.2.1.1 Calibration of images
In order to measure the size of a cell, images had to be calibrated. This was
accomplished using Image J software along with a calibration slide. The slide contained
15 micron beads, and when loaded into Image J, a line was traced across the diameter of the
bead. A measurement of the line provided a value in pixels, and since the diameter of the bead
49
was known, we obtained a value of pixels / µm. This value was then applied to all subsequent
images.
2.2.1.2 Determining size of the cell
The size or area of a given cell was determined using the same protocol as in 2.4.3,
where a line was traced around the visible perimeter of the plasma membrane. This procedure
was repeated for all cells in the field of view, and then added to the ROI manager in Image J.
From here the measurements for size (µm2) were extracted and loaded into SPSS for analysis.
2.2.1.3 Determining shape of a cell
The cells used in these analyses were attached to the glass dish, which means that they
each varied in shape to a certain degree. Image J offers a measurement of circularity, which is
described in equation 2.2 below. This provides a unitless value with a range from 0 to 1, with
1 indicating a perfect circle.
𝐶𝑖𝑟𝑐𝑢𝑙𝑎𝑟𝑖𝑡𝑦 = 4𝜋 𝑥 𝐴𝑟𝑒𝑎
𝑃𝑒𝑟𝑖𝑚𝑒𝑡𝑒𝑟2
Equation 2.2 - Determining the shape of a cell. A predetermined parameter provided
by image J software providing a measure of sphericity. Unitless values are computed from 0 –
1, where 1 indicates a perfect circle.
2.2.1.4 Determining the angle of the cell with respect to the applied electric field
The ROI manager in Image J also provides a measurement of angle. This is a
calculation that initially measures the long and short axes of the plasma membrane, and then
measures the angle in degrees between the x axis of the image and the cell’s long axis. Once
this data was extracted, a correction was made for the positioning of the electrodes.
2.2.1.5 Determining the density of cells in a given image
After each cell had been traced a final ROI was traced around the entire field of view,
which was also added to the ROI manager. The density of cells per unit area (cells / µm2) was
50
then calculated simply by dividing the number of cells in the field of view by the area of the
image.
2.2.2 Statistical analyses
The statistical tests used in this chapter were based on the assumptions of a parametric
dataset. As such, various criteria had to be met prior to performing these tests. These
assumptions have been outlined in the general methods section of the introductory chapter
and are detailed in [81].
2.3 Results
From a large sample size of 500 U87 cells collected over a multitude of experiments
and over a three year period, variables such as cell size (µm2), circularity of cell (1 indicating a
perfect sphere), angle (degrees) relative to the direction of the applied electric field, and
density of cells in the field of view (cells per µm2) were extracted. These factors were
subsequently entered as predictors into a linear multiple regression. The outcome variable was
relative change in membrane potential, which was measured using PMPI.
Two variables were able to account for a small proportion of the change in Vm following
nsPEF. Circularity (n = 500, X = 0.78, SD = 0.10, p < 0.01) and density (n = 500, X = 0.0015,
SD = 0.0008, p = 0.02) entered the statistically significant model [F(2 , 497) = 6.65, p < 0.01,
Ω2 = 0.02]. The relationship can be represented by (Eq. 2.3). This equation, as would be
expected, highlights a positive relationship with circularity and a negative relationship with
cell density. In other words, the greatest change in Vm post nsPEF would be expected under
conditions where fewer cells were present and when those cells were more spherical than
irregularly shaped.
51
𝑉𝑚 = 88.4𝑥 − 9157.9𝑦 + 54.9
Equation 2.3 – Equation describing relationship between cell shape and density
with PEF-induced membrane depolarization. Here, Vm is measured as relative change
in PMPI fluorescence; x refers to the shape (circularity); and y refers to density.
It is interesting that the statistically significant model was only able to account for
approximately 2 % of the change in Vm following nsPEF exposure. In other words, that
majority of the variability in membrane depolarization is unaccounted for using the factors
entered into the regression. Moreover, factors such as cell size and orientation to the electric
field failed to significantly contribute to the model.
After carefully looking through the data, something became apparent that wasn’t
noticed during the initial analysis. When considering the baseline fluorescence, there was a
clear grouping of data points (Fig 2.4). To test if this represented two statistically different
groups, a sequence of tests was performed. To begin, a cluster analysis was performed on the
baseline fluorescence data. Consistent with our observations, the results from the cluster
analysis divided the data into 2 groups, where 465 cells were in the first group and the other
35 cells were in the second group.
Using the groups generated from the cluster analysis, a discriminant function analysis
was performed to determine if these groups were truly statistically different from one another.
The results from this test revealed a discriminant function that explained 92% of the variance
between groups. This function significantly differentiated the baseline fluorescence data [Λ =
0.15, χ2(1) = 946.82, p < 0.01].
52
Figure 2.4 - Investigating pattern in baseline fluorescence. Two distinct clusters are
easily distinguishable when examining baseline fluorescence values. X (average of first 5
minutes pre-pulse) and y (first 2.5 minutes post-pulse) values are given in raw fluorescence
values.
These results suggest that there were two populations of cells that were significantly
different from one another despite having identical experimental protocols. Moreover, these
cells weren’t clustered temporally, meaning they represent two distinct populations that have
been collected over several years. What could be different about these cells then? Referring to
table 2.1 and 2.2 below, you will find descriptive statistics for the two groups along with a
correlation table which describes their relationship with the factors used in the multiple
regressions.
Cluster 1 Cluster 2
53
Sample size (n)
Minimum Maximum Mean Standard deviation
Cluster 1
Area (µm2) 465 15.09 538.62 87.05 58.56
Baseline fluorescence
465 12.55 465.64 88.48 84.38
Circularity 465 0.36 0.96 0.77 0.10
Angle (degrees)
465 0.25 179.76 95.66 51.50
Density (#/µm2)
465 9.70 10-5 2. 10-3 1.54 10-3 8.54 10-4
Cluster 2
Area (µm2) 35 33.33 363.48 126.24 74.08
Baseline fluorescence
35 543.81 1237.91 958.54 172.66
Circularity 35 0.65 0.90 0.80 0.08
Angle (degrees)
35 0.13 177.49 92.32 46.94
Density (#/µm2)
35 2.91 10-4 2.82 10-3 1.48 10-3 4.56 10-4
Table 2.1 - Descriptive statistics for the two populations of cells grouped by
baseline fluorescence. For each parameter investigated, this table provides the sample size
(n), minimum, maximum, and mean values, as well as the standard deviation for both clusters
of cells.
54
Fluorescence change
Area (µm2)
Fluorescence baseline
Circularity Angle (degrees)
Density (#/µm2)
Cluster 1 0.106 0.424 0.123 0.029 -0.107
Cluster 2 -0.160 -0.446 0.069 0.238 -0.072
Table 2.2 - Pearson correlation table from the multiple regression test divided
into clusters. Values in bold indicate a statistically significant correlation between those
values and the change in fluorescence using an alpha of 0.05.
Interpretation of the above two tables provides insight into the difference between
groups. Beginning with the descriptive statistics (Table 2.1), aside from the different baseline
fluorescence values, the average values from all other factors are essentially identical.
Important differences are seen, however, when we refer to the correlation table (Table 2.2).
Despite being the same cells treated in the exact same way, the first cluster is comprised of
cells that are depolarized more as the size of the cell increases; which is contrasted in the
second cluster, where depolarization is more pronounced as the size of the cell decreases.
The same pattern follows when considering the baseline values. Keeping in mind that
the baseline values are representative of the resting membrane potential, cells in cluster 1 have
a tendency to be more influenced by exposure to the nsPEF as the baseline fluorescence
increases (less negative resting membrane potential); whereas cells in cluster 2 tend to be
more influenced as the baseline fluorescence decreases (more negative resting membrane
potential).
2.4 Discussion
Since the 1950’s, electrophysical models have described the interaction between an
applied electric field and a biological membrane. These have been extremely useful in
designing experiments and interpreting results. Yet, despite multiple discrepancies between
55
theoretical predictions and experimental data in the literature, the established theory has not
been challenged.
Of course these models are based off well established physical laws of
electromagnetism described eloquently by Maxwell in the mid 1800’s; however, application of
these theories into biology tends to require that a cell is reduced from a complex living thing
to a capacitor floating in conductive solution.
Molecular dynamics (MD) simulations have been a technological breakthrough that
allow us to investigate electric field effects on the individual molecules making up a cell. Yet
despite this incredible tool, the programs that determine the output are all designed based off
the same fundamental theories. One advantage of MD is modeling a dynamic structure as
opposed to the static electrophysical resistor-capacitor model. The cost of this, however, is the
requirement for tremendous computational power limiting our search to a small fraction of
the cell membrane and for a very short period of time.
The goal of this chapter was to investigate how theoretical models hold up against a
large experimental dataset. Membrane potential was selected as the outcome variable because
according to the literature, the induced transmembrane potential is the first step in a series of
biological events following electropulsation [17, 18].
The results from this section suggest that under these conditions, there
appears to be additional variables that are contributing to the nsPEF-induced
membrane depolarization. Factors such as cell size, shape, orientation to the electric field
and the density of cells being exposed failed to account for more than 90 % of variability in
membrane depolarization following nsPEF exposure.
So, what other factors could account for this variability? One possibility could include
ion channels. This idea was first explored almost 30 years ago [93], where microsecond pulses
were found to influence the activity of Na+/K+ pump in human erythrocytes. Later, evidence
was presented suggesting ms-PEF may induce electro-conformational damage to voltage-gate
56
channels [94]. Despite these findings, researching the potential role of ion channels in PEF-
effects has just recently began to resurge. Several studies have now shown that voltage-gated
ion channels can be activated by nsPEF [63–65].
Directly related to the activity of voltage-gated channels, the cell cycle could provide
additional clues regarding variability in data from PEF experiments. Cells constantly oscillate
through periods of de- and hyperpolarization, associated with changes in ion channel
conductivity, that have been directly correlated with specific phases of the cell cycle [95–97].
When we consider results [89] demonstrating that membrane permeability was
significantly greater following PEF exposure of cells in the S – M phase of the cell cycle
compared to those in the G1 phase, it may not be spurious that we found two statistically
distinct groups of cells clustered by baseline fluorescence (resting membrane potential).
Furthermore, the 90/10 split between clusters is in line with the proportion of time primary
carcinomas [98], and specifically U87 cells [99], spend in G1 phase versus S, G2 and M phases.
Even If we assume that our clusters are representative of groups of cells divided into G1 and S
– M phases, several key differences make it is difficult to compare our results to those in [89];
namely different pulse durations (µs vs ns), measured outcomes (permeability vs membrane
potential), and cell type used (yeast vs human cells).
With that said, more attention should be given to expanding our understanding of
electric field – cell membrane interactions. This is most important when we are looking at cell
effects over longer periods of time. Combining the results presented here, along with some of
the recent research discussed above, the influence of PEFs on transmembrane ion channels
and perhaps even the role of cell cycle effects seem like good candidates for future studies.
57
Chapter 3:
Nanosecond pulsed electric fields
depolarize transmembrane poten-
tial via voltage-gated K+, Ca2+ and
TRPM8 channels in U87
glioblastoma cells.
(Based on published manuscript)
58
3.1 Introductory Remarks
The following chapter is based on the manuscript [100]. It is worth noting that
additional experiments have been included here that were not present in the manuscript.
When considering the effects of PEF on complex living cells, the most fundamental process to
begin our investigations would be the transmembrane potential (Vm). The reason it is
imperative to understand the interaction of an electric field with the cell’s resting membrane
potential is because the superposition of the applied electric field on the cells Vm is considered
to be the initial factor influencing cell behavior [17, 18] .
nsPEFs have a variety of applications in the biomedical and biotechnology industries.
Cancer treatment has been at the forefront of investigations thus far as nsPEFs permeabilize
cellular and intracellular membranes leading to apoptosis and necrosis. nsPEFs may also
influence ion channel gating and have the potential to modulate cell physiology without
poration of the membrane. This phenomenon was explored using live cell imaging and a
sensitive fluorescent probe of transmembrane voltage in the human glioblastoma cell line, U87
MG, known to express a number of voltage-gated ion channels. The specific ion channels
involved in the nsPEF response were screened using a membrane potential imaging approach
and a combination of pharmacological antagonists and ion substitutions. It was found that a
single 10ns pulsed electric field of 34 kV/cm depolarizes the transmembrane potential of cells
by acting on specific voltage-sensitive ion channels; namely the voltage and Ca2+ gated BK
potassium channel, L- and T-type calcium channels, and the TRPM8 transient receptor
potential channel.
3.2 Introduction
Nanosecond pulsed electric fields (nsPEFs) have been exploited in applications such
as cancer therapy [66, 101, 102], and have demonstrated promise in improving gene delivery
when combined with conventional pulses [103, 104]. In vitro experiments [27, 69, 105–107]
59
along with support from mathematical modeling [32, 62, 108] have demonstrated that nsPEFs
cause changes in cell physiology by permeabilization of the plasma membrane and
intracellular organelles. Results have also been demonstrated in vivo with considerable nsPEF
effects on tumor growth [55] and vascular perfusion [109]. A prominent mechanistic working
model developed from MD simulations suggests that nsPEF permeabilization is mediated by
the reorganization of water molecules at the lipid membrane interface by the electric field-
induced orientation of their dipoles, leading to the formation of pores [110].
Few experimental studies or simulations have considered the potential role of
transmembrane pore-forming protein complexes and channels in nsPEF effects. A wide
variety of such ion channels exist in the plasma membrane that can influence membrane
permeability to ions and small molecules and can be gated by a wide range of stimuli ranging
from ligands (ionotropic receptors), voltage (voltage-gated ion channels), mechanical
perturbation (mechanosensitive ion channels) or changes in temperature (transient receptor
potential channels (TRPs)).
In vitro studies have primarily investigated the permeabilization of the plasma
membrane by nsPEF using the translocation of small membrane-impermeant fluorescent
molecules, fluorescent ion sensors, or electrophysiology. The latter, more direct approach of
measuring plasma membrane impedance using the patch-clamp technique was used to probe
membrane resistance following the application of nsPEFs (60 ns, 12 kV/cm), revealing a
threefold decrease in membrane resistance 80 - 120 seconds following pulse delivery with a
gradual recovery over 15 minutes [105]. Several ion channel pore blockers and ion
substitutions were used in these experiments to examine the selectivity and specificity of the
membrane permeability to various ionic species. Although this study did support MD theory
of membrane permeabilization, the authors were careful to differentiate permeabilization and
poration, and concluded that there was not sufficient evidence to confirm the creation of
aqueous pores.
60
A subsequent study examined the size and lifetime of nanopores at the level of the
plasma membrane. These experiments compared the effects of nsPEF (600 ns, 0.75-10.2
kV/cm) on the uptake of small fluorescent molecules (YO-PRO, propidium iodide PI) vs the
uptake of Thallium (Tl+) [111]. This investigation followed previous studies [69, 112] which
demonstrated that more intense electric field strengths were required to observe PI uptake
versus YO-PRO uptake. It was concluded that the larger PI molecules were occluded from
pores where the smaller YO-PRO molecules passed through. Because of its small size (< 1 nm),
Tl+ uptake showed the presence of even smaller nanopores from which YO-PRO and PI would
be excluded. The results from this study, combined with previous findings, suggested that
nsPEF exposure led to pores smaller than 1 nanometer.
Some studies have considered the possibility that such short pulsed electric fields could
influence ion channel behavior. This alternative to electroporation was first explored in bovine
chromaffin cells using a pulse protocol of 5 ns, 50 kV/cm [64]. By using several
pharmacological inhibitors of calcium and sodium channels, it was shown that a combination
of L- N- and P/Q-type calcium channel blockers abolished the nsPEF-induced influx of
calcium into cells, suggesting the involvement of voltage-gated calcium channels.
In a separate study, the effects of PEF’s was examined on several cell lines [63] using a
pulse duration of 500 picoseconds at 190 kV/cm, with a range of pulses up to 100 at a
frequency of 200 Hz or 1 kHz. When applying these pulse parameters to CHO cells, which
served as a negative control due to the lack of voltage-gated channels, no effects were observed
while measuring [Ca2+]i with Fura-2. Yet when tested on cell lines known to contain voltage-
gated channels, such as GH3 and NG108, the same protocol resulted in a significant increase
in [Ca2+]i. To demonstrate this effect was not due to electroporation of the plasma membrane,
voltage-gated calcium channel blockers, verapamil (L-type) and w-Conotoxin (N-type) were
utilized. While these pharmacological inhibitors could partially block the calcium response
when used separately, as a cocktail they could block 85 - 100 % of the observed PEF response.
61
These results imply that the calcium increase caused by ultrashort pulsed electric fields was
mediated by voltage-gated calcium channels.
The distinction between direct permeabilization effects on the plasma membrane and
changes in ion permeability mediated by voltage-gated ion channels is important, given that
many cancers are known to express voltage-gated ion channels [113, 114]. We therefore chose
to investigate the influence of nsPEFs on the human glioblastoma cell line (U87), as it
expresses many types of ion channels that are characterized at the level of gene expression
[115] and in detailed electrophysiological recordings [116, 117]. Our working hypothesis was
that if nsPEF-induced membrane permeabilization was due to electroporation and the
formation of nanopores, the response would not be inhibited by specific pharmacological
inhibitors of ion channels. We tested this hypothesis using a fluorescent indicator of
transmembrane potential to screen a wide range of ion channel inhibitors for their ability to
inhibit a plasma membrane depolarization response caused by a single, 10 ns pulsed electric
field of 34 kV/cm.
3.3 Materials and Methods
3.3.1 Pharmacological manipulation of ion channel activity
Multiple ion channel agonists/antagonists were used to monitor their effects on
nsPEF-induced membrane depolarization. These drugs were selected based on their ability to
block channels known to be present in this cell line [97, 116–121]. All ion channel modulators
were purchased from Sigma Aldrich and are summarized by activity in table 3.1 below.
62
Product Concentration Mechanism of action
Incubation period
Calcium channel modulators
A784168 10 µM TRPV1 blocker 15 minutes
AMTB Hydrate 50 µM TRPM8 channel blocker
15 minutes
BAPTA-AM 10 µM, 30 µM IC Ca2+ chelator 45 minutes
Cyclopiazonic acid 1 µM Ca-ATPase blocker/depletes ER
10 minutes
Ethylene glycol tetraacetic acid (EGTA)
1.8 mM (replaced CaCl2)
EC Ca2+ chelator 15 minutes
Gadolinium 10 µM Broad calcium and TRP channel antagonist
15 minutes
HC-030031 3 µM to 300 µM TRPA1 blocker 15 minutes
Ionomycin 10µM Ca2+ ionophore Added prior to imaging
Lanthanum chloride (LaCl3)
100 µM Broad calcium channel antagonist
15 minutes
M8-B 2 nM to 50 µM TRPM8 channel blocker
15 minutes
Mibefradil 20 µM T-type VGCC blocker 15 minutes
Nifedipine 10 µM L-type VGCC blocker 15 minutes
Ruthenium Red 100 µM Broad calcium channel antagonist
15 minutes
2-APB 100 µM TRPC blocker 15 minutes
Potassium channel modulators
Barium chloride (BaCl2)
2.5 mM (replaced KCl) KIR channel blocker 15 minutes
Clotrimazole 30 µM IK channel blocker 15 minutes
Glibenclamide 50 µM ATP-dependent K+ channel blocker
15 minutes
Iberiotoxin 10 nM BK channel blocker 15 minutes
63
Paxilline 100 µM BK channel blocker 15 minutes
Penitrem A 100 nM to 10 µM BK channel blocker 15 minutes
Phloretin 30 – 1000 µM BK activator Added prior to imaging
Tetraethylammonium chloride (TEA)
5 mM to 100 mM Voltage-gated K+ channel blocker
15 minutes
Sodium channel modulators
Amiloride HCl 200 µM Na+ channel blocker; ASIC blocker; mechanogated ion channel blocker
15 minutes
Tetrodotoxin (TTX) 1 µM Voltage-gated Na+ channel blocker
15 minutes
Choline Chloride 140 mM Used to replace sodium in imaging media
15 minutes
N-methyl-D-glucamine (NMDG)
140 mM Used to replace sodium in imaging media
15 minutes
Table 3.1 - List of pharmacological agents used throughout this investigation.
Product names are given along with the concentrations used and their mechanism of action.
For clarification of abbreviations: TRP = transient receptor potential, IC = intracellular, EC =
extracellular, CaMKII = Calcium/calmodulin-dependent protein kinase II, VGCC = voltage-
gated calcium channel, KIR = inward-rectifying potassium channel, IK = intermediate
conductance calcium-dependent potassium channel, BK = big conductance calcium-
dependent potassium channel, ASIC = acid-sensing ion channel.
3.3.2 Calibration of PMPI voltage-dye
In order to obtain information regarding membrane potential from fluorescence data
the fluorophore (PMPI) needed to be calibrated. Cells were incubated in the same method as
above; however, several imaging solutions were made where the concentration of NaCl was
replaced by increasing amounts of KCl (2.5 mM, 25 mM, 50 mM, 100 mM, and 140 mM). An
64
estimate of membrane potential was then computed by applying the Goldmann equation and
comparing the fluorescence data at various K+ concentrations with the calculated membrane
potential at those concentrations. Although semi-quantitative in nature, this method allowed
for a general estimate of the changes in membrane potential over time following exposure to
nsPEF.
The results from the calibration were compared to separate results calibrating PMPI
using patch-clamp electrophysiology (section 3.4.1). Here, cells were exposed to a voltage-
ramp while PMPI fluorescence was measured. With these results, we were able to compare
both quantitative and semi-quantitative measures of transmembrane potential and use this
data to estimate the magnitude of depolarization following electric field exposure.
3.3.3 Statistical analyses
Statistical analysis was performed using IBM SPSS 19. Assumptions were met for
analysis using parametric tests. More detail on the individual statistical analyses can be found
in the general methods section of the introductory chapter, in addition to [81].
3.4 Results
3.4.1 Calibration of PMPI
The first step in our investigation was to calibrate PMPI. Although semi-quantitative
in nature, using different calibration methods it should be possible to determine a change in
transmembrane potential in response to a stimulus. This is different than knowing the
absolute value of the transmembrane potential at a given moment; however, knowing how
much a given manipulation is altering Vm is still useful for interpreting effects. PMPI
calibration was performed using potassium [K+] gradients and additionally using patch-clamp
electrophysiology.
65
3.4.1.1 Potassium calibration
Calibration of the dye using K+ was achieved by monitoring the change in relative
fluorescence over time using varying concentrations of extracellular K+. For a period of 30
minutes, imaging medium was exchanged every 5 minutes with [K+] from 2.5 mM to 140 mM
(Fig. 3.1). Maximum depolarization of the transmembrane potential occurred following the
addition of 100 mM [K+].
Figure 3.1 - Calibration of PMPI by varying extracellular K+. Relative fluorescence
changes for PMPI were measured over time in response to increases in extracellular [K+].
Potassium concentration was gradually increased from 2.5 mM to 140 mM with a step
occurring every 5 minutes Results are the average from 5 experiments. Error bars represent
+/- 2 SE
Because we were most interested in the change in relative fluorescence at different
concentrations of extracellular [K+], a linear regression was performed to determine the
relationship between variables. It should be noted that maximum depolarization occurred at
100 mM; therefore, the 140 mM data was not entered into the regression because no useful
information could be obtained. The relationship between relative fluorescence and
66
extracellular [K+] can be summarized using Eq. 3.1 below in which 96 % of the variability can
be explained by the relationship between variables.
𝑦 = 0.0993𝑥 − 0.479 , 𝑅2 = 0.96
Equation 3.1 – Equation describing relationship between extracellular
potassium concentration and membrane depolarization between 0 and 100 mM
[K+]. A linear regression was performed to find a relationship between relative fluorescence
and the extracellular [K+].
3.4.1.2 Calibration using electrophysiology
The next step involved a similar approach as above, using patch-clamp
electrophysiology. Cells (n = 4) were exposed to a voltage-step ranging from -90 mV to +10 mV
for five minutes and the relative fluorescence was recorded. The results obtained from these
experiments were best fit using a 2nd order polynomial expression, which is summarized in
equation 3.2 below, where the experimental manipulation accounted for 99% of the variability.
This equation suggests that every increase in 1 relative fluorescent unit is associated with a
membrane depolarization equivalent to 22.7 mV.
𝑦 = 0.0052𝑥2 − 0.1198𝑥 + 1.0402 , 𝑅2 = 0.99
Equation 3.2 – Equation describing relationship between membrane potential
and PMPI fluorescence. A 2nd order polynomial equation was best able to explain the
relationship between the transmembrane potential (mV) and the relative fluorescence
measured.
PMPI calibration using two methods should allow us to generate a semi-quantitative
estimate regarding the PEF effects on Vm. Table 3.2 below provides a comparison of the
relative fluorescence changes using K+ calibration and electrophysiology. The last column
67
provides an estimation, using the Goldman-Hodgkin-Katz (GHK) equation (Eq 3.3), of the
transmembrane potential changes associated with alterations of the extracellular potassium
concentration. Results from both electrophysiology and GHK estimation of the Vm are seen in
columns 2 & 4. Relative fluorescence changes using PMPI under both calibration methods
result in very similar (+/- 4 mV) changes in Vm.
𝑉𝑚 =𝑅𝑇
𝐹 ln (
𝑝𝑘 [𝐾+ ]𝑖 + 𝑝𝑁𝑎 [𝑁𝑎+ ]𝑖 + 𝑝𝐶𝑙 [𝐶𝑙− ]𝑖
𝑝𝑘 [𝐾+ ]𝑜 + 𝑝𝑁𝑎 [𝑁𝑎+ ]𝑜 + 𝑝𝐶𝑙 [𝐶𝑙− ]𝑜)
Equation 3.3 – Goldmann equation. Describes the predicted membrane potential based
on the concentrations of ions inside [X]i and outside [X]o of the cell, where X is Na+, K+, or Cl-
, in addition to factors such as membrane permeability (p) of a give ion species, The gas
constant (R), Faraday’s constant (F) and the temperature (T).
Relative fluorescence
(ΔF/Fo)
ΔVm (mV) Ephys
[K+]o ΔVm (mV)
GHK estimation
1 22.7 14.9 18
2 29.3 25.0 26
3 34.1 35.0 32
4 38.0 45.1 37
5 41.4 55.2 42
6 44.5 65.2 45
7 47.3 75.3 48
8 49.9 85.4 51
Table 3.2 - Comparison between calibration methods for PMPI. This table
summarizes the membrane potential change following nsPEF delivery for both the
electrophysiology and potassium calibration.
3.4.2 Determining the threshold of electric field intensity required for nsPEF-induced membrane depolarization.
In order to determine the threshold for membrane depolarization, electric field
intensity was varied (16.5 kV/cm, 22 kV/cm, 34 kV/cm, and 44 kV/cm). When comparing the
68
group means 2.5 minutes post pulse, significant group differences were observed. Applied
electric field strengths of 16.5 kV/cm or 22 kV/cm were not significantly different than the no
pulse conditions, although the latter was qualitatively different. Both the 34 kV/cm and 44
kV/cm applied field strengths were significantly different than control conditions (Fig. 3.2).
In each case, membrane depolarization caused by a single 10 ns pulse was transient,
recovering in 15 - 20 minutes.
Figure 3.2- Determining the electric field threshold for a single nsPEF to
depolarize plasma membrane. An analysis of variance indicated there was a significant
difference in relative fluorescence between groups exposed to different electric field strengths
[F (4, 26) = 27.82, p < 0.01, Ω2 = 0.80]. Post hoc analysis followed using the Games-Howell
method. Significant membrane depolarization was observed when using applied field
strengths of 34 kV/cm [n = 5, X = 2.85, SE = 0.17, p < 0.01, r = 0.99] and 44 kV/cm [n = 5, X
= 2.90, SE = 0.56, p < 0.01, r = 0.97] when compared to control conditions [n = 8, X = 0.01,
SE = 0.02]. When field strength was reduced to either 22 kV/cm [n = 5, X = 0.89, SE = 0.31]
or 16.5 kV/cm [n = 5, X = 0.001, SE = 0.03] no significant effect was observed, though a visible
qualitative response in the 22 kV/cm condition. Pulse deliver occurred at 5 minutes and is
indicated by arrow in figure. Error bars represent +/- 2 SE
69
3.4.3 Fluorescence imaging of plasma membrane depolarization following a single 34 kV/cm nsPEF.
One of the most conspicuous features of the membrane potential dye (PMPI) is its
unequal distribution within the cell. The 2-part dye responds to changes in membrane
potential by entering or exiting the cell. During depolarization, the anionic, charged
component enters the cell resulting in an increase in fluorescence (Fig. 3.3 a, b). This response
is reversed during repolarization as the charged molecules exit the cell and interact with the
quenching agent present in the extracellular space thereby decreasing the fluorescence.
Figure 3.3 - Fluorescence imaging of U87 cells prior to and after delivering a
single nsPEF with an electric field intensity of 34 kV/cm. PMPI is a two-part indicator
of membrane potential consisting of an anionic, charged component and a quenching agent
restricted to the extracellular space. Upon depolarization of the plasma membrane, the
charged molecules enter the cytosol and increase in fluorescence intensity. Pseudo-colored
images are shown for enhanced contrast. a and b depict the fluorescence change pre vs. post
pulse. c is a surface plot montage of the selected region in a framed by the square. The nsPEF
was delivered after five minutes, corresponding to the tenth image of the montage marked by
the arrow. Maximum depolarization can be seen after 60 seconds and individual regions of
70
intense depolarization are observed throughout the remainder of the experiment at different
time points. d is an example taken from the surface plot highlighting the geometry of these
punctate regions where depolarization of membrane potential first occurs in response to the
nsPEF (x and y axes are given in micrometers, while the z axis is in raw fluorescence changes).
3.4.4 Inhibition of nsPEF depolarizing effect with BK channel blockers.
In order to investigate the role of ion channels in the nsPEF depolarization, multiple
ion channel antagonists were tested for their ability to abrogate the response to a single
34 kV/cm nsPEF. If depolarization was mediated by pores, then none of the pharmacological
channel-blockers would be expected to inhibit the response. The following section investigates
the influence of nsPEF on a subtype of voltage-dependent potassium channels.
U87 cells are known to express several potassium channels, many of which are voltage
dependent. Because the observed depolarization was slow, taking place over minutes, non-
voltage-gated channel antagonists were also used. Inhibitors of voltage-and-calcium-
dependent potassium channels were found to inhibit the depolarization of the plasma
membrane caused by a single nsPEF (fig. 3.4 below). When inhibitors of voltage-and-calcium-
dependent potassium channels (BK, SK, IK), Inward rectifying potassium channels (KIR) and
ATP-dependent potassium channels (KATP) were compared with nsPEF-only conditions, there
was a statistically significant difference in their ability to abrogate the nsPEF depolarization
(fig. 3.4 below).
Prior to depolarization, the dye can be seen clustering into small, punctate regions.
Although the spatial distribution of labelling varied in each cell, the clusters accounted for
roughly 15 - 20 percent of the observable plasma membrane, with the small punctate regions
ranging from 0.5 - 1.0 µm in diameter (fig. 3.3 c, d).
71
Post-hoc analysis using Games-Howell method indicated the source of the significant
difference was between the nsPEF only condition and those cells pretreated with 10 μM
Penitrem A and 100 mM TEA. No significant differences were observed between nsPEF
depolarized cells and cells those treated with any of the other inhibitors. Results are presented
in Fig. 3.4 below.
Figure 3.4- Effects of potassium channel blockers on nsPEF-induced membrane
depolarization. An analysis of variance indicated there was a significant difference between
the mean fluorescence between groups using different potassium blockers [F (6, 64) = 17.09,
p < 0.01, Ω2 = 0.60]. Post hoc analysis using the Games-Howell method revealed the
following: when comparing control conditions (nsPEF only) and those with potassium
channel blockers, only Penitrem A, a specific BK channel blocker [n = 5, X = 0.75, SE = 0.26,
p < 0.01, r = 0.96]; and 100 mM TEA, a broad voltage-gated potassium channel blocker (KV)
[n = 16, X = 0.58, SE = 0.26, p < 0.01, r = 0.96] significantly inhibited membrane
depolarization from a single 34 kV/cm, 10 nsPEF. Inhibiting ATP-dependent (KATP) channels
with Glibenclamide [n = 9, X = 2.73, SE = 0.27], small conductance voltage-and-calcium
dependent potassium (SK) channels with 5 mM TEA [n = 5, X = 2.42, SE = 0.18], intermediate
conductance voltage-and-calcium dependent potassium (IK) channels with 30 μM
Clotrimazole [n = 11, X = 2.55, SE = 0.09], or inward rectifying potassium channels (KIR) with
2.5 mM Barium chloride (BaCl2) [n = 10, X = 2.24, SE = 0.40] produced no significant
72
differences from controls. Asterisks * represents statistical significance at alpha = 0.05
compared to nsPEF only condition. Error bars represent +/- 2 SE
Whereas the 100 mM TEA condition significantly inhibited the nsPEF-induced
depolarization, the 5 mM TEA did not. Since it is known that KV inhibition at high
concentrations (> 10 mM) of TEA are known to include BK channels but not at low
concentrations (≤ 10 mM) [116], a range of TEA concentrations were used next to investigate
the dose-response of the TEA inhibition of the nsPEF depolarization. A statistically significant
trend can be seen, whereby increasing concentrations of TEA inhibited the nsPEF-induced
membrane depolarization (Fig. 3.5).
Figure 3.5 - Concentration-dependent inhibition of nsPEF depolarization by TEA.
Comparing the nsPEF-induced membrane depolarization measured using increasing
concentrations on tetraethyl ammonium (TEA) compared to the control conditions showed
significant group differences [F (5, 46) = 25.32, p < 0.01, Ω2 = 0.72]. Post hoc analysis using
Games-Howell test were conducted. Whereas 5 mM [n = 5, X = 2.42, SE = 0.18] TEA
concentrations did not have statistically significant effects on nsPEF-induced depolarization,
a linear trend can be seen as concentrations increase reaching statistical significance at 10 mM
[n = 7, X = 1.58, SE = 0.15, p = 0.02, r = 0.69], 20 mM [n = 5, X = 1.13, SE = 0.34, p = 0.02, r
= 0.87], 50 mM [n = 5, X = 0.68, SE = 0.22, p < 0.01, r = 0.84], and 100 mM [n = 15, X = 0.57,
73
SE = 0.08, p < 0.01, r = 0.96] TEA. Asterisks * represents statistical significance at alpha =
0.05 compared to nsPEF only condition. Error bars represent +/- 2 SE
Post-hoc analyses using Games-Howell reveal that statistically significant nsPEF
inhibition was observed in conditions using 10 mM, 20 mM, 50 mM, and 100 mM TEA
concentrations, but not with conditions using 5 mM TEA.
Since results from experiments using high concentrations of TEA and those using the
selective BK channel blocker, Penitrem A, suggest that BK channel blockers can inhibit the
nsPEF-induced membrane depolarization; two additional BK channel blockers were
investigated: 100 μM Paxilline and 10nM Iberiotoxin. When compared to the nsPEF only
condition BK channel block resulted in statistically significant inhibition of nsPEF-induced
depolarization (Fig. 3.6a). Post-hoc analysis using Games-Howell indicated that Paxilline but
not Iberiotoxin was able to significantly inhibit depolarization following nsPEF.
If the nsPEF application was depolarizing transmembrane potential via activating the
BK channel, as suggested by the inhibition of these effects by BK inhibitors, one would also
expect that activation of the BK channel by pharmacological agonists should produce similar
changes in PMPI as induced by nsPEF. To confirm this, a specific activator of the BK channel
was used without any exposure to pulsed electric fields. When 10 μM Phloretin was added to
gate the BK channel, a depolarization was observed that was statistically similar to that
observed following nsPEF (Fig. 3.6b).
74
Figure 3.6 - BK channel blockers significantly inhibit membrane depolarization
following 34 kV/cm nsPEF. a- An analysis of variance indicated there was a significant
difference in mean fluorescence between groups [F (4, 49) = 27.79, p < 0.01, Ω2 = 0.70]. Post
hoc analysis followed using the Games-Howell method. When comparing nsPEF only
conditions to those with Paxilline [n = 5, X = 0.35, SE = 0.25, p < 0.01, r = 0.94] and
Iberiotoxin [n = 15, X = 2.64, SE = 0.26], only the condition with 100 μM Paxilline significantly
inhibited the nsPEF-induced depolarization. b- A two-tailed t-test comparing relative
fluorescence measures indicated there was no significant difference between group means [t(2
tail)(11) = 0.32, p = 0.75] when 10 μM of Phloretin [n = 4, X = 3.26, SE = 0.14] was added to the
external media, compared to the response observed when cells were exposed to nsPEF [n = 9,
X = 3.10, SE = 0.32]. Data for tetraethyl ammonium chloride (TEA) and Penitrem A are
included from figure 4. Asterisks * represents statistical significance at alpha = 0.05 compared
to nsPEF only condition. Error bars represent +/- 2 SE
75
3.4.5 Depolarizing response of nsPEF is calcium-sensitive.
Among the potassium channel blockers explored, BK channel blockers were the only
ones able to significantly inhibit membrane depolarization following nsPEF application. Its
role was confirmed by using specific BK channel activators which mimicked the response
observed following pulse application. Given that the BK channel can be gated by voltage-and-
calcium, it was expected that modulating calcium should influence the sensitivity of the
response to nsPEF. To test whether modulating intracellular and extracellular calcium
concentrations could influence the threshold depolarization response following nsPEF,
experiments were conducted using the following parameters: calcium-free conditions were
performed with cells that were incubated with 10 μM BAPTA–AM and 1.8 mM Ethylene glycol
tetraacetic acid (EGTA) substituted for 1.8 mM calcium chloride; and conditions where 10 μM
of the calcium ionophore Ionomycin was added.
As represented in Fig. 3.7, altering the concentration of calcium shifted the threshold
of the electric field intensity required for depolarization. In the control condition (n = 25), the
EF50 (electric field required for 50 % maximal depolarization response) was determined to be
26.15 kV/cm where a maximal response was considered 100 %: A significant shift to the left
was observed in the Ionomycin condition (n = 19) where the EF50 was 20.34 kV/cm and the
maximal response exceeded the control by 10 %, whereas in the calcium-free condition (n =
21) the EF50 was shifted significantly to the right to a value of 45.43 kV/cm with the maximal
response being less than 50 % of that under control conditions. Descriptive statistics for these
results can be found in Table 3.3.
76
Figure 3.7 - Calcium-dependent threshold response curves in response to nsPEF
of varying electric field strengths. Removing extracellular and intracellular calcium
resulted in an EF50 (electric field intensity required to produce 50 % of the maximal
depolarization) of 45.43 kV/cm (blue trace) and reduced the maximal response to less than 50
% of that observed in control conditions where the EF50 was determined to be 26.15 kV/cm
(black trace). An opposite shift in EF50 of 20.34 kV/cm (red trace) was observed using the
calcium ionophore Ionomycin, which also resulted in a 10 % increase in maximal response
compared to control conditions. The overall fit for these dose-response curves was very good
with statistically significant differences between groups [χ2 (2) = 0.38, p < 0.01, Adj. R2 = 0.99].
Error bars represent +/- 2 SE
77
Electric field strength (kV/cm)
Control Calcium-free Ionomycin
Baseline n = 8, X = 1.87, SE = 0.47
n = 3, X = 0.93, SE = 0.40
n = 4, X = 2.58, SE = 0.76
16.5 n = 3, X = 2.47, SE = 1.02
n = 3, X = 1.56, SE = 0.21
n = 3, X = 10.38, SE = 1.70
22 n = 4, X = 30.73, SE = 10.78
n = 5, X = 5.42, SE = 1.22
n = 4, X = 75.30, SE = 19.38
34 n = 5, X = 91.93, SE = 8.56
n = 5, X = 25.40, SE = 3.06
n = 3, X = 100.94, SE = 14.83
44 n = 5, X = 100.00, SE = 8.56
n = 5, X = 46.01, SE = 10.60
n = 5, X = 114.03, SE = 9.42
Table 3.3 - Descriptive statistics from figure 3.7. Sample sizes (n), means (X), and
standard errors (SE) are included by calcium condition for each level of electric field strength
used.
Knowing that calcium was important for the nsPEF depolarizing effect, subsequent
experiments were undertaken to determine whether the source of the calcium; being either
extracellular (EC), intracellular (IC) or via release from the endoplasmic reticulum (ER)
played a role in the amplitude of the response. These experiments were separated into
extracellular calcium-free, intracellular calcium-free, and ER depleted; and these were
compared to both the controls and the calcium-free (IC+EC) results above. Cells were
incubated with 1.8 mM Ethylene glycol tetraacetic acid (EGTA), which was substituted for the
calcium chloride in the media for the EC calcium-free condition; whereas for the IC calcium-
free condition cells were incubated with 10 µM BAPTA-AM; and for the ER calcium-depleted
procedure cells were incubated with 1 µM Cyclopiazonic acid (Fig. 3.8).
Whereas conditions using 1 µM Cyclopiazonic acid were not significantly different than
controls, removing calcium from the extracellular and intracellular environment resulted in
significant inhibition that was statistically similar to those observed when removing EC and
IC calcium. Although removing EC and IC calcium resulted in significant inhibition of the
nsPEF-induced membrane depolarization, the greatest effect was observed when EC calcium
was removed.
78
Figure 3.8 - Comparing the role of calcium from intracellular, extracellular and
endoplasmic reticulum compartments. An analysis of variance indicated there was a
significant difference in average fluorescence between groups [F (4, 41) = 16.44, p < 0.01, Ω2
= 0.60]. Post hoc analysis followed using the Games-Howell method. Significant differences
in depolarization were observed when comparing controls with 1.8 mM calcium in media [n =
9, X = 3.10, SE = 0.32] to conditions where EC calcium was removed by substituting 1.8 mM
EGTA for calcium in the media [n = 7, X = 0.88, SE = 0.11, p < 0.01, r = 0.95], IC calcium was
removed by adding 10 µM BAPTA-AM [n = 10, X = 1.28, SE = 0.18, p < 0.01, r = 0.89], or both
[n = 5, X = 0.74, SE = 0.09, p < 0.01, r = 0.96]; however, no significant effect was observed
when calcium from the ER was depleted using 1 µM Cyclopiazonic acid [n = 11, X = 2.44, SE =
0.27]. Asterisks * represents statistical significance at alpha = 0.05 compared to nsPEF only
condition. Error bars represent +/- 2 SE
79
Next, to test whether the influence of calcium on the depolarizing response was solely
due to its role in modulating BK channel function or by nsPEF modulation of voltage-gated
calcium channels, a series of experiments using several calcium channel blockers were
performed (Fig. 3.9). Broad calcium entry channel blockers, Gadolinium, Lanthanum chloride
and Ruthenium Red were investigated; as were L-type calcium channel blocker Nifedipine and
T-type calcium channel blocker Mibefradil. Calcium can also enter via non-voltage-gated
calcium channels such as the family of transient receptor potential (TRP) channels; therefore,
selective TRPA1 blocker HC030031, TRPV1 blocker A784168, TRPC blocker 2-APB, and
TRPM8 blockers M8-B and AMTB hydrate were tested for the capacity to block the nsPEF
depolarization response.
Analysis revealed a statistically significant difference between conditions. Post hoc
analyses using Games-Howell method revealed a significant inhibition of membrane
depolarization between 10 µM Nifedipine, 20 µM Mibefradil, combined 10 µM Nifedipine and
20 µM Mibefradil, 100 µM Gadolinium, 100 µM Ruthenium Red, 100 µM Lanthanum
chloride, 100 µM 2-APB, 50 µM M8-B, and 50 µM AMTB hydrate conditions when compared
with controls. Conversely, no significant differences were observed between control conditions
and those using 300 µM HC030031 or 10 µM A784168.
80
Figure 3.9 - Effects of calcium channel blockers on nsPEF-induced membrane
depolarization. An analysis of variance revealed a significant difference in mean
fluorescence between groups [F (11, 91) = 11.71, p < 0.01, Ω2 = 0.56]. Post hoc analysis were
then performed using the Games-Howell method. Conditions using 10 µM of TRPV1 blocker
A784168 [n = 9, X = 3.43, SE = 0.42], or 300 µM of TRPA1 blocker HC030031 [n = 6, X =
2.38, SE = 0.41] produced no significant differences from control conditions [n = 9, X = 3.10,
SE = 0.32]. Significant inhibition of nsPEF-induced membrane depolarization was observed
in conditions using broad calcium channel blockers 100 µM Gadolinium [n = 9, X = 1.69, SE
= 0.12, p = 0.04, r = 0.70], 100 µM Ruthenium Red [n = 7, X = 1.43, SE = 0.23, p = 0.04, r =
0.71] and 100 µM Lanthanum chloride [n = 7, X = 1.07, SE = 0.33, p = 0.02, r = 0.83]; with
the selective L-type calcium channel blocker 10 µM Nifedipine [n = 6, X = 1.41, SE = 0.14, p =
0.02, r = 0.90], T-type calcium channel blocker 20 µM Mibefradil [n = 8, X = 0.81, SE = 0.23,
p < 0.01, r = 0.91], or when 10 µM Nifedipine was combined with 20 µM Mibefradil [n = 4, X
= 0.71, SE = 0.29, p < 0.01, r = 0.93]; as well as with TRPC blocker 100 µM 2-APB [n = 9, X =
1.57, SE = 0.19, p = 0.03, r = 0.69], or TRPM8 blockers 50 µM M8-B [n = 5, X = 0.88, SE =
0.28, p < 0.01, r = 0.91] and 50 µM AMTB hydrate [n = 9, X = 0.44, SE = 0.18, p < 0.01, r =
0.95]]. Asterisks * represents statistical significance at alpha = 0.05 compared to nsPEF only
condition. Error bars represent +/- 2 SE
81
3.4.6 nsPEF-induced membrane depolarization is not mediated by voltage-gated Na+ channels; however, Na+ ions may still be involved.
With evidence that nsPEF depolarization responses were abrogated by inhibitors of
voltage-gated K+ and voltage-gated Ca2+ channels, the following section investigated inhibitors
of voltage-gated Na+ and Cl- channels. For these experiments 1 µM of Tetrodotoxin (TTX) and
200 µM of Amiloride hydrochloride were used to block voltage-dependent Na+ channels.
Further tests were performed by removing extracellular Na+ and replacing it with equimolar
140 mM N – methyl – D - glucamine (NMDG) or Choline chloride.
The results from this series of investigations revealed (Fig. 3.10) a significant difference
in group means. It should be noted that the assumption of homogeneity of variance was not
met as determined using Levene’s test; therefore, Welch’s F test was used as a correction. Post
hoc analysis using Games-Howell test showed no significant differences between conditions
using TTX or Amiloride HCl when compared with controls. In contrast, removing extracellular
sodium using either NMDG or Choline chloride significantly inhibited membrane
depolarization caused by nsPEF.
These results, however, are difficult to interpret given that both NMDG and Choline
chloride are known to block BK channel activity [122, 123]. Confirmation of this fact is evident
in the same analysis where 10 µM Phloretin was applied in the presence of Choline chloride
and the depolarizing effect observed above, which was on the same order of magnitude as that
observed following nsPEF delivery, was abolished.
82
Figure 3.10 - Comparing effects from sodium and chloride channel blockers on
nsPEF-induced membrane depolarization. An analysis of variance, reporting Welch’s
F due to a violation of the assumption of homogeneity of variance, revealed a significant
difference in mean depolarization responses between groups [F (6, 20.3) = 61.69, p < 0.01, Ω2
= 0.70]. Post hoc analysis using the Games-Howell method found no significant effects on
depolarization response following nsPEF delivery when comparing control conditions [n = 9,
X = 3.10, SE = 0.32] to those with voltage-gated sodium channel blockers 1 µM TTX [n = 7, X
= 2.96, SE = 0.25] and 200 µM Amiloride hydrochloride (HCl) [n = 8, X = 2.93, SE = 0.69].
Conversely, when sodium was replaced in the extracellular media there was significant
inhibition of the membrane depolarization using either N – methyl – D - glucamine (NMDG)
[n = 9, X = 0.53, SE = 0.11, p < 0.01, r = 0.96] or Choline chloride [n = 9, X = 0.51, SE = 0.05,
p < 0.01, r = 0.97]. Repeating the experiments with Choline chloride in the presence of the BK
channel activator Phloretin 10 µM resulted in inhibition of the depolarizing response [n = 10,
X = 0.04, SE = 0.02, p < 0.01, r = 0.98]. Error bars represent +/- 2 SE
83
3.4.7 nsPEF-block is reversible.
In order to demonstrate that the inhibitors used were in fact inhibiting the nsPEF-
induced membrane depolarization, we first had to rule out the possibility that the inhibitors
were depolarizing the cells during the incubation period. If they were indeed depolarizing the
cells they would not have the ability to further depolarize in response to nsPEF, which could
explain nsPEF depolarization-inhibition. This possibility was ruled by applying multiple
pulses at five minute intervals and observing the response over time. After three initial pulses,
the imaging solution containing the inhibitor was washed off and replaced with the control
solution (Fig. 3.11).
Figure 3.11 - Reversibility of the TEA and Penitrem A inhibition of the nsPEF-
induced membrane depolarization. A single 34 kV/cm nsPEF (n = 9) was delivered every
5 minutes (indicated by black arrows in figure) while the TEA (n = 15)/Penitrem A (n = 6)
(solution was replaced with control solution after 17.5 minutes (indicated by black bar in
figure) demonstrating that the inhibition of the nsPEF-induced depolarizing response was not
due to any depolarizing effect of inhibitors during incubation. For the purpose of clarity, only
the 10 µM Penitrem A and 100 mM TEA data is displayed. Reversibility of the response was
consistent among other inhibitors. Error bars represent +/- 2 SE
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Following the removal of the pharmacological inhibitor, subsequent nsPEF delivery
produce depolarizing response expected in the control conditions. This reversibility of the
nsPEF block demonstrates that the cells were not depolarized during incubation and that the
inhibitors used were in fact inhibiting the plasma membrane depolarization following nsPEF
application. Another important feature is that repolarization of the resting membrane
potential could be prevented by applying a subsequent pulse every five minutes.
3.5 Discussion
The purpose of this investigation was to study the role of voltage-gated ion channels in
the depolarization response of the transmembrane potential following delivery of a single 10
nanosecond pulsed electric field. A combination of pharmacological inhibitors and a
fluorescent indicator of plasma membrane potential was used with live cell imaging to evaluate
the role of the various ion channels expressed in human U87 glioblastoma cells. These intense,
short duration pulsed electric fields are known to exert their influence on cell physiology by
inducing a transmembrane voltage across the cell leading to the formation of pores in the
plasma membrane and intracellular organelles. This study implicated several ion channels in
the nsPEF response and pharmacologically discriminated the specific voltage-gated channels
involved.
The membrane potential indicator (PMPI) we employed in our investigations has
previously been used in several studies and has been shown to be a valuable tool for
monitoring membrane potential with higher throughput than patch clamp electrophysiology
[77, 124, 125]. Our calibration of PMPI fluorescence with transmembrane potential was
consistent with previous studies that compared PMPI fluorescence using electrophysiology
[126].
By using a wide range of ion channel blockers and ion substitutions, we have provided
strong evidence that the application of a single nsPEF is directly modulating ion channels
within the parameters used in this study (10 ns pulse, 34 kV/cm). With that said, these results
85
may at first appear to be somewhat contrary to what one would expect. It is counterintuitive
that the BK channel would gate at a negative resting membrane potential in the absence of
Ca2+ as we have observed with nsPEF depolarization; however, this has been reported in non-
excitable cells and the mechanism is well characterized [127]. The BK channel is primarily a
hyperpolarizing channel and blocking the BK channel would be expected to increase the
depolarizing effect observed; however, multiple studies have demonstrated that blocking the
BK channels could have an inhibitory effect on depolarization and neurotransmitter release
[128–130]. Interestingly, the BK channel has been demonstrated in some cells to operate in a
biphasic mode [131, 132]. In excitable cells such as neurons, the activation of BK channels
induces a hyperpolarizing response leading to a decrease in intracellular calcium and closing
of voltage-gated calcium channels creating a negative feedback loop. Conversely, in non-
excitable cells activation of BK results in increased intracellular calcium through activation of
non-voltage gated calcium channels thereby increasing the driving force of calcium, and
creating a positive feedback loop.
It is worth noting that the dimensions of punctate depolarized clusters and “hotspots”
observed in PMPI labelling are consistent with previously measured size and distribution of
lipid rafts within the cell membrane [133, 134]. From a physiological perspective, it is well
established that many ion channels including voltage-gated ion channels are commonly
clustered in lipid rafts [117, 134]. Specifically the BK channel has been shown to form
complexes with T-type calcium channels [135] and L-type calcium channels [136].
The positive-feedback relationship between calcium channels and BK channels
explains the results presented in this work and can be summarized as follows: Activation of T-
type and L-type voltage-gated calcium channels by the nsPEF generates an inward calcium
current which results in activation of BK channels. Activation of voltage-gated calcium
channels has been confirmed previously with 5 ns, 50 kV/cm pulses [64] and shorter 500 ps,
190 kV/cm pulses [63]. Here, BK activation creates an outward potassium current which can
activate calcium influx through non-voltage-gated calcium channels [131, 132], in the case of
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U87 cell, where TRPM8 channels are known to interact with BK channels in glioblastoma cells
[137]. It is also possible that the nsPEF could simultaneously activate BK channels and voltage-
gated calcium channels. The fact that using a specific BK channel activator could depolarize
the cells to a similar degree as the nsPEF corroborates this possibility (Fig. 3.12).
Figure 3.12 - Proposed mechanism of direct interaction between nsPEF and
voltage-gated channels along with downstream effects on non-voltage dependent
channels. 1. A single 10 ns, 34 kV/cm nsPEF activated voltage-gated calcium channels (L and
T-type) along with the voltage- and calcium-dependent BK channels, causing an influx of Ca2+
and efflux of K+. 2. The K+ efflux then triggers further Ca2+ entry through non-voltage-gated
cation channels (TRPM8). 3. This action establishes a positive feedback loop and results in
further membrane depolarization.
Considered the “gold standard” for studying BK channel activity, the lack of inhibitory
action of the selective BK channel blocker, Iberiotoxin, was an unexpected result. However,
reviewing the literature shed light on this apparent mystery. Toxin resistant BK channels have
87
been described since the late 1980’s [138]. Originally found to be insensitive to Charybdotoxin,
these channels are also insensitive to Iberiotoxin, which is a closely related toxin [139].
As a general overview of the BK channel, it consists of a tetrameric assembly of alpha
subunits (BKα), which are responsible for creating the pore forming domain, and also contain
the calcium biding domain and voltage sensing domain. Co-expressed with the alpha subunits
are auxiliary beta subunits which are known to modulate the channel’s activity [132, 140, 141].
The resistance to toxins is due to the presence of a specific isoform of the beta subunit (β4),
which is known to be widely expressed in the brain [142–144]. Moreover, glioblastoma cells
are known to express a specific subtype of BK channel known as the glioma BK or gBK [117],
which incidentally are also known to express the Iberiotoxin-and-Charybdotoxin resistant β4
subunit [145].
It was not possible to definitively rule out Na+ in the nsPEF transmembrane
depolarization response, although it was clear from our results that voltage-gated Na+
channels were not involved. When Na+ was removed from the extracellular media and replaced
with equimolar NMDG+ or Choline+, the depolarizing effect of Phloretin was eliminated. This
result makes sense as both NMDG+ and Choline+ are also known to inhibit BK channel activity
[122, 123, 146, 147]. It is of interest that TRPM8 channels were found to have a role in the
nsPEF depolarization response as they are permeable to divalent and monovalent cations
[148–151]. BK activation with TRPM8 gating would undoubtedly transport Na+ in addition to
Ca2+ into the cell and this would be commensurate with recent electrophysiological studies
that have identified Na+ currents in the early stage of nsPEF effects [152].
The involvement of TRP channels in the depolarization response caused by nsPEFs
was also an important finding as some of the TRP channels are known to dilate to form pores
permeable to small cationic fluorescent molecules such as YO-PRO-1 and ethidium. TRPA1,
TRPV1 and TRPM8 are cell sensors for thermal, chemical and mechanical stimuli that are also
known to form large, stable and reversible pores [149, 153], intriguingly similar to those caused
by nsPEFs. Our investigation showed TRPM8 inhibition partially abrogated the nsPEF
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depolarization response. It is still controversial whether TRPM8 form large pore complexes
[154], and pore dilation is more confirmed with TRPA1 and TRPV1 [154–156]; so future studies
should consider the influence of nsPEFs on pore-dilating TRPs as these are also known to be
upregulated in cancer [113, 137].
BK channels (Big Potassium, also called Maxi-K or slo1), are a potentially important
target for nsPEF effects as they have currents in order of 100-300 picoSiemens [157] and they
are known to be upregulated in glioma and many other types of cancer [158, 159]. BK
activators are also known to lead to apoptosis [160]. Mechanistically, it is not clear whether
electric pulses in the nanosecond timescale could directly open BK channels as their gating
time at physiological voltages requires multiple states with an activation time constant in the
order or 150-200 microseconds [161]. Certain isoforms of BK channels are also known to be
sensitive to mechanical stimulation and membrane stretch [162]. Further investigations
should consider the mechanical properties of both BK and TRP channels in nsPEF effects,
given that these stimuli have recently been shown to generate pressure transients [163].
Finally, we have also demonstrated that a single nsPEF delivered at five minute
intervals can depolarize and prevent reestablishment of the resting membrane potential of
U87 glioblastoma cells. Experiments are underway exploring the long-term manipulation of
transmembrane potential to determine if non-electroporating nsPEFs can disrupt cell
physiology in a manner that may be therapeutically useful for the treatment of cancer. The
repolarization of plasma membrane potential in cancer cells repeatedly depolarized by nsPEF
would be expected to occur via the Na+/K+-ATPase at great energetic cost, and given that only
cancer cells expressing voltage-gated ion channels would be sensitive to this treatment, this
may represent a new means to bioelectrically exhaust cancer, while sparing non-malignant
cells nearby.
3.6. Conclusion
The primary aim of this section was to investigate the possibility that nsPEF are
acting on transmembrane ion channels. A single 10 nsPEF was used at varying electric field
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intensities to explore this. We monitored the transmembrane potential using the commercial
indicator, PMPI, which proved to be a useful tool for studying long-term effects. Using a
variety of pharmacological modulators of ion channel activity, we found that voltage-gated
potassium and calcium channels were intimately connected to the observed depolarization
following nsPEF exposure, as was the TRPM8 cation channel. Blocking these channels
resulted in a significant decrease in membrane depolarization post-nsPEF exposure. We
provided a potential theoretical model explaining how the interconnectivity between these
channels, that are often found in proximity in lipid rafts, could help explain our results.
Because the expression of ion channels varies significantly among cell lines, nsPEF effects
would most likely be explained by different ion channels in different cells.
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Chapter 4 -
Plasma membrane depolarization
and permeabilization due to electric
pulses in cell lines of different
excitability
91
4.1 – Introductory remarks
The following chapter has been adapted from a manuscript that is currently under
revision. This was a collaborative project between our lab and the University of Ljubljana.
Results presented will include only those to which I directly contributed. Three cell lines were
used for the following experiments: U87 glioblastoma cells, CHO cells, and HT22 mouse
hippocampal neurons. HT22 cells were used in their differentiated and non-differentiated
states. Experiments were conducted using pulse durations ranging from 10 ns up to 10 ms,
where membrane potential and membrane integrity were the outcome variables measured.
For both variables, the goal was to determine the threshold, or the lowest electric field
intensity, required to depolarize or permeabilize the cells.
The bigger picture for these experiments was to test the potential for optimizing
current treatments using electropermeabilization, such as electrochemotherapy. One common
complaint for electrically based therapies is the associated discomfort due to the electrical
excitation of the surrounding muscle and nervous tissues, which leads to muscle contractions
and pain. We investigated whether it would be possible to find an electric field intensity that
could simultaneously permeabilize the target tissues while minimizing the excitation of the
surrounding nerves and muscles.
We found a statistically significant difference in excitability between cell types.
Although the electric field threshold required to permeabilize the cells did not differ
significantly between cell lines, the differentiated neurons required a stronger electric field to
depolarize their transmembrane potential compared to the other cell lines. Although this was
an in vitro study, these results indicate that it may be possible to modulate the electric field
intensity in a clinical setting to enhance permeabilization, while limiting the excitation of
neighboring nerves and muscles, thus the sensation of pain.
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4.2 Introduction
Short, high-voltage pulses have been shown to increase the permeability of cell membranes
to different molecules (reversible electroporation) or cause cell death (irreversible
electroporation - IRE) [164–166]. Electropermeabilization is used in biotechnology sectors for
food-processing [167–169], and in medicine [170] for gene electrotransfer (GET) [37, 48, 171],
DNA vaccination [172–175], transdermal drug delivery [176, 177], IRE as a soft tissue ablation
technique [42, 45, 46, 178] and electrochemotherapy (ECT) [179–182].
Medical applications of electroporation extend to a variety of tissues and tumours. Some
of these tissues are electrically excitable, such as neurons in the central and peripheral nervous
systems as well as muscle tissues. These cells are known to undergo sponataneous electrical
activity [183] which is how they communicate with other tissues, and these excitable cells may
be particularily vulnerable to electrically-based treatments.
In the literature, there are several examples of ECT, IRE and GET targeting excitable
tissues using electric pulses. Brain cancer has been treated with IRE, and electric pulses have
been shown to transiently disturb the blood-brain-barrier allowing chemotherapeutics to
enter the brain [44, 184–188]. Treating prostate cancer [43, 189], bone metastases [179, 190],
and tumours in the spine can affect the surrounding nervous tissue [190]. When treating
tumours in other parts of the body, electrodes will invariably be in the vicinity of the nerves or
muscles where the electric field is high enough for excitation or even permeabilization. Electric
pulses are also used for ablation of myocardial tissue to treat atrial fibrillation [191–193].
Muscles are a popular target for gene electrotransfer as they are easily accessible and
transfected [194, 195]. Among them, the heart can be electroporated to treat ischemia [196,
197].
Several studies have shown that the effect of electric pulses on the functionality of excitable
tissues was only short-term. Following IRE, nerves in different animal models recovered
electro-physiologically, histologically and functionally [190, 198–200] or at least showed a
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potential for regeneration [201]. After electroporation of neurons within the rat neocortex , in
vitro and in vivo, the membrane potential, the action potential waveform and passive
membrane properties remained unchanged [202]. Following pulmonary vein ablation using
electroporation, the histology and functionality of phrenic nerve remained unchanged [203].
Finally, no histological damage on nerves in the neurovascular bundle was observed post-IRE
treatment of the prostate [199].
Some of the main drawbacks to treating tissues with pulsed electric fields are; the pain
associated with repeated electrical stimulation [204–207], the need to administer muscle
relaxants and anaesthesia [208] and synchronization with the ECG [209–211]. The neurons
responsible for pain sensation are also known as nociceptors and have been shown to be
stimulated by electric pulses [212, 213]. An important advancement for PEF treatments would
be to determine a point at which maximum permeability of the membrane could be achieved
while minimizing excitation of the nearby excitable cells. In ECT, for example, this would
translate to maximum drug delivery into tumour cells with minimum tissue damage to
surrounding regions, reduced pain experienced by the patient, and minimal use of muscle
relaxants.
The following experiments will explore how pulsed electric fields will effect excitable and
non-excitable cells. This will be addressed using measures of membrane potential and
membrane permeability for pulse durations ranging from 10 ns to 10 ms. Using a range of
electric field intensities, the goal will be to determine the lowest intensity required to
depolarize the transmembrane potential and to permeabilize the plasma membrane. The
results will be compared between cell types to determine whether or not it could be possible
to optimize current treatments to reduce the sensation of pain due to repeated electrical
stimulation.
94
4.3 Materials and Methods
Some of the materials and methods are common between thesis chapters. These include
cell culture, growth and maintenance; fluorescence microscopy, pulse generators and
electrodes used; data extraction from images, as well as statistical methods used to analyze
data. In the interest of not repeating information, these have been explained in detail in the
general methods section of the introductory chapter.
4.3.1 Cell culture and preparation
Three cell lines were used (Fig. 4.1) for the following experiments. CHO Chinese
hamster ovary cells (Fig. 4.1a), U87 human glioblastoma cells (Fig. 4.1b), and HT22
immortalized mouse hippocampal neurons. The HT22 cell line was used in their non-
differentiated and differentiated states. Following differentiation, morphological changes
were evident and the cells stopped dividing (Fig. 4.1 c vs d).
4.3.2 Potassium calibration of PMPI.
A chemical calibration was performed for all cell types to determine their degree of
excitability. This was accomplished by measuring membrane depolarization (PMPI
fluorescence) in conditions with increasing [K+] in the imaging solution (2.5 mM, 25 mM, 50
mM, 75 mM, 100 mM, 140 mM). Osmolarity was maintained by removing NaCl in an
equimolar manner as KCl was increased. Each sample was monitored continuously with the
buffer being replaced every 5 minutes.
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Figure 4.1 - Phase-contrast images of all four cell lines used in experiments. a –
CHO; b - U87 MG; c - undifferentiated HT22; and d - differentiated HT22. All images were
taken at 200x magnification.
4.4 Results
4.4.1 Cell Excitability
The first experiment compared how each cell line responded to chemical depolarization by
increasing the extracellular [K+] over time (Fig. 4.2). Here we found that the greatest relative
change in membrane potential occurred in the CHO cell line. U87 cells and the
undifferentiated HT22 cells responded almost identically, whereas the differentiated HT22
cells showed the least amount of relative change. The four cell lines began to show the greatest
divergence when the 50 mM [K+] buffer was added.
96
Figure 4.2 – Chemical depolarization of cells using K+. Fluorescence changes were
monitored in all four cell lines. The imaging solution was changed every 5 minutes with
increasing [K+] ranging from 2.5 mM in the original imaging solution up to 140 mM. Error
bars represent +/- 2SE.
A representative response to the depolarization dynamics following pulsed electric field
exposure can be seen in (Fig. 4.3). A similar trend was observed for all pulse durations, where
the U87 cells showed the greatest depolarization and the differentiated HT22 cells showed the
least. One exception to this was in the 10 ms condition, where the CHO cells were depolarized
more than all other cells. The maximal depolarization was observed within the first 2.5
minutes following pulse exposure, after which the membrane potential gradually returned to
near baseline levels. The time for repolarization differed based on the magnitude of
depolarization but ranged anywhere from 5 – 25 minutes.
97
Figure 4.3 – Representative depolarization dynamics following PEF
exposure. Membrane depolarization was observed after a single 10 ns PEF of 44 kV/cm,
with the exception of the differentiated HT22 cells requiring a minimum of 52 kV/cm to
depolarize the transmembrane potential. Error bars represent +/- 2SE.
Figure 4.4 – Magnitude of depolarizing response to pulsed fields from 10 ns
– 10 ms. U87 cells show a greater response to PEF-induced membrane depolarization
compared to all cells, but they also show the greatest variability. Error bars represent +/-
2SE.
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Another interesting feature is highlighted in Fig. 4.4, where the U87 cells not only show
the largest depolarization response, but they also show the greatest variability in their
response. In some cases, such as the 1 µs duration, U87 cells had 5 times more variability than
the other cell lines. An ANOVA was performed comparing the variance between cells, which
confirmed that the variability in the U87 cell line was statistically greater than the other cells
[F(3, 27) = 4.19, p = 0.01, Ω2 = 0.24].
Fig. 4.5 shows the strength-duration curve for depolarization of all cell lines. The exact
values are listed in Table 4.1. We can see that an inverse relationship between the threshold
and pulse duration is evident, such that longer pulses require a much lower electric field to
elicit a depolarizing response. The statistical parameters for the analyses of the depolarization
threshold are shown in the Supplementary data section (Table S1 and S2).
Table 4.1 - The depolarization thresholds for all tested pulse durations and cell
lines. The results listed here are a tabular representation of the data in Fig. 4.5. The asterisk
(*) denotes that the threshold for this condition had to be estimated due to the large variability
of the data. All data is presented in kV/cm.
Electric field (kV/cm)
Pulse duration 10 ns 550 ns 1 μs 10 μs 100 μs 1 ms 10 ms
CHO 44 2.0 1.2 0.45 0.30 0.15 0.10
U-87 MG 34 2.2 1.4 0.60 0.35 0.20 0.12
Undifferentiated HT22
34 2.0 1.4 0.70 0.50 0.35 0.24
Differentiated HT22
52 2.0 1.7* 0.90 0.60 0.40 0.28
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Figure 4.5 - The strength-duration curve for depolarization thresholds of all cell
lines. The minimum electric field intensity required to depolarize the transmembrane
potential is given for all pulse durations tested in kV/cm. As the pulse duration increases, the
electric field required to depolarize the cell decreases.
4.4.2 Plasma Membrane Permeability
The normalized plasma membrane permeabilization curve to YO-PRO is shown for all four
cell lines in Fig. 5.6. The threshold for electropermeabilization (Fig. 4.6a) in U87 and CHO
cells was 0.4 kV/cm, whereas it was slightly higher (0.6 kV/cm) for the undifferentiated and
differentiated HT22 cells. A similar increase in permeabilization was seen for all cell lines as
the electric field strength increased. The permeabilization curve could be best described using
a symmetric sigmoid (Fig. 4.6b). Table 4.2 summarizes some of the parameters from the curve,
which show that all four cell lines reached 50% permeabilization (E50%) between 0.8 and 0.9
kV/cm.
100
Figure 4.6 - Normalized permeabilization curve of all four cell lines to YO-PRO,
5 min after the pulse application. The threshold for electroporation was reached at
0.4 kV/cm (U-87 MG and CHO) or 0.6 kV/cm (undifferentiated and differentiated HT22
cells). a) Normalized values, the error bars represent one standard deviation and b) the fitted
symmetric sigmoid. Normalized fluorescence fn/- is presented as a function of applied electric
field E/(kV/cm).
An example of the time dynamics for YO-PRO uptake following 8 x 100 μs pulses at
1.2 kV/cm is shown in Fig. 4.7a. The maximal fluorescence and the resealing dynamics (τ) were
extracted by fitting a first-order uptake model. The maximal fluorescence (Fig. 4.7b) was the
highest for the U-87 MG cells and the lowest for the CHO cells. There were no significant
differences in maximal fluorescence between the differentiated and undifferentiated HT22s,
while all other pairwise comparisons using a t-test yielded statistically significant differences.
The value of time constant τ (Fig. 4.7c) corresponds to the time when 63% of the pores in the
membrane resealed. The resealing was the fastest for the U-87 MG cells, similar for the
undifferentiated HT22s and CHO cells, and slowest for the differentiated HT22 cells.
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Figure 4.7 - Time dynamics of YO-PRO uptake and analyses. a - Time dynamics of
the YP uptake for all four cell lines following 8 x 100 µs pulses at 1.2 kV/cm and 1 Hz repetition
frequency. Error bars represent one standard deviation. Fluorescence (arbitrary units) is
presented as a function of time (min). b - The maximal value of YP fluorescence (arbitrary
units) for all four cell lines. c - The resealing constant (τ/s) is presented for each cell line. Error
bars for b and c represent the 95% confidence interval.
Cell line E50% (kV/cm) b (kV/cm) R-squared
CHO 0.80 ± 0.06 0.15 ± 0.11 0.98
U-87 MG 0.81 ± 0.10 0.13 ± 0.09 0.99
HT22 undifferentiated 0.94 ± 0.07 0.12 ± 0.06 0.99
HT22 differentiated 0.91 ± 0.07 0.12 ± 0.06 0.99
Table 4.2 - Parameters of the fitted symmetric sigmoid to the normalized data of
YO-PRO uptake. The numbers listed denote the optimal value and the corresponding 95%
confidence intervals.
4.5 Discussion
The goal of this study aimed to compare the depolarization thresholds between excitable
and non-excitable cells. For each cell, the strength-duration curve was determined, using the
obtained threshold values, following exposure to a single pulse ranging in duration from 10 ns
102
to 10 ms. The permeability curve was also determined for each cell line following application
of 8 x 100 µs pulses, delivered at 1 Hz. For the assessment of cell depolarization we used the
PMPI dye. For the assessment of the plasma membrane permeabilization we used YO-PRO
(YP) dye.
PMPI is a valuable tool for the measurement of membrane potential [125] and ion channel
pharmacology [214, 215]. Although electrophysiology is considered the gold standard for
measurement of membrane potential, PMPI has several advantages, namely the ease of use,
the ability to monitor long-term changes, and the ability to monitor multiple cells
simultaneously. Furthermore, PMPI has been compared directly to electrophysiology data
with a good agreement [126]. It consists of a two-part system which includes a fluorescent
anionic voltage-sensor and a quencher. When a cell is depolarized, the sensor translocates
across the plasma membrane resulting in an increase in fluorescence. Conversly, the
quenching molecule is excluded from the cell. With that said, when the plasma membrane is
permeabilized, it could be possible for the quenching molecule to enter the cell through pores
formed in the membrane and decrease the fluorescence in the cell. Interestingly, when pulses
were applied well above the depolarization threshold, we observed a decrease in the
fluorescent signal which could be indicative of cell electroporation. In the future, it should be
established to what extent the PMPI dye could also serve as cell membrane permeabilization
indicator.
The results following electrochemical depolarization show that with increasing K+
concentration, the fluorescence and thus the transmembrane voltage are increasing which is
in agreement with theory. It was unexpected, however, that the highest fluorescence was
achieved in CHO cells and not with the differentiated HT22 cells. Excitable cells typically have
a higher density of voltage-gated channels, thus more ions should enter the cell when these
channels are open. CHO cells are non-excitable cells and would be expected to have a low
expression of voltage-gated ion channels; however, some reports indicate that these cells
express voltage-gated Na+ channels [216] and voltage-gated Ca2+ channels [217].
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CHO cells have a resting membrane potential around - 10 mV [218], which is similar to
that of U87 cells [116]. Although electrophysiology studies on HT22 cells were not found, a
typical neuron has a resting potential around – 70 mV [219]. If we recall from the previous
chapter, the depolarizing response measured here would be associated with a change in
magnitude less than 30 mV. One possibility could be that the resting potential of the neurons
did not reach the threshold required to activate voltage-gated channels.
The relatively low resting potential of the U87 cells combined with the large complement
of voltage-gated channels [116] could explain why the U87 cells experienced the greatest
depolarizing effect to one pulse. It is also worth noting that cancerous tissues have been shown
to be more affected by PEFs than non-cancerous tissues [220, 221].
The repolarization time for all four cell lines was in the range of minutes. Certainly this
was most surprising when considering the differentiated neurons which normally would be
expected to have repolarization times in the millisecond range [219]. There are several possible
explanations for the longer-than-expected repolarization time. First, as the assessment
method, we used PMPI dye, which has a time constant of several seconds [222]. Second, our
experiments were performed at room temperature which would be expected to slow down the
kinetics of the Na+/K+ pump. Third, it is possible that cells were depolarized as well as
electroporated. If true, electroporation has been reported to cause leakage of ATP [223] which
is necessary for repolarizing the membrane. Fourth, due to such a high induced
transmembrane voltage (several volts), it is possible that ion channels could be damaged
[224].
The time required for reaching the peak fluorescence in depolarization experiments
coincided with the resealing time observed in the permeabilization experiments. It is possible
that during depolarization and permeabilization experiments, PMPI and YP were entering
through voltage-gated channels [154] as well as through pores formed in the plasma
104
membrane. Even when using channel inhibitors, a total inhibition of depolarization could not
be achieved which indicates that during depolarization ions also enter through pores [100].
In the next part of our study, we exposed cells to 8 x 100 μs pulses, which are typically used
in electrochemotherapy treatments. All four cell lines reached the threshold of electroporation
at approximately the same value - between 0.4 and 0.6 kV/cm. The permeabilization curve of
all four lines could be described using a symmetric sigmoid. Although differentiation of HT22
cells causes a drop in the resting membrane potential [225], the more negative resting
membrane potential did not affect the threshold for electroporation. The permeabilization
curves followed similar dependency and reached 50% of the maximal fluorescence around
0.9 kV/cm. We can conclude that irrespective of the cell’s excitability, all four cell lines
responded similarly to electroporation pulses.
The YO-PRO uptake was the greatest in the U87 cell line and least in CHO cells. As
mentioned previously, cancerous cell have been shown to be more susceptible to PEFs when
compared to non-cancerous cells which could explain why they were the most permeabilized.
Since the cells were grown attached in a monolayer, the reason CHO cells showed the least
YO-PRO uptake could be due to the tendency of CHO cells to grow in colonies in close
proximity which decreases the area of the plasma membrane available for dye uptake. The
close proximity of cells could have also decreased the induced transmembrane potential due
to shielding [226–228].
4.6 Conclusion In summary, the depolarization threshold was higher for the excitable cells than for the
non-excitable cells. All four cell lines responded similarly to pulses of standard
electrochemotherapy parameters. The shape of the permeability curve was similar to curves
already published in the literature [229]. Thus, electroporation is a feasible means of treating
excitable and non-excitable cells with pulses of similar parameters. Furthermore, our results
show the potential of achieving permeabilization and minimizing or avoiding excitation/pain
105
sensation which needs to be explored in more detail. In future studies, it should be established,
however, to what extent in vitro depolarization and excitability correlate to the actual
excitation and pain sensation in vivo.
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Supplementary Data
Table S1 - Statistical parameters for the strength-duration curve by cell line. F(x,
y) = ANOVA score with degrees of freedom in parentheses. Fw = Welch’s F adjustment when
the assumtion of homogeneity of variance was not met. The statistical significance provides
the p-values which are compared to our alpha criterion of α = 0.05. The effect size column
provides the proportion of variation in response attributed to the PEF.
CHO
ANOVA Significance Effect size (Ω2) 10 ns F (2 , 17) = 9.00 p < 0.01 0.47 550 ns F (3 , 15) = 4.56 p = 0.02 0.36 1 µs F (3 , 16) = 91.52 p < 0.01 0.93 10 µs FW (3 , 6.08) = 14.12 p < 0.01 0.67 100 µs F (4 , 19) = 10.35 p < 0.01 0.61 1 ms FW (3 , 5.55) = 53.76 p < 0.01 0.89 10 ms F (3 , 13) = 10.80 p < 0.01 0.63
U87
ANOVA Significance Effect size (Ω2) 10 ns F (4 , 19) = 2.90 p < 0.01 0.80 550 ns F (3 , 15) = 3.60 p = 0.04 0.29 1 µs F (3 , 16) = 4.32 p = 0.02 0.33 10 µs FW (4 , 9.27) = 43.54, p < 0.01 0.63 100 µs F (3 , 21) = 47.64 p < 0.01 0.85 1 ms FW (4 , 6.62) = 13.96 p < 0.01 0.71 10 ms F (3 , 19) = 10.66 p < 0.01 0.56
Undifferentiated HT22
ANOVA Significance Effect size (Ω2) 10 ns FW (3 , 3.06) = 21.88 p = 0.01 0.81 550 ns F (2 , 9) = 12.96 p < 0.01 0.67 1 µs F (3 , 9) = 11.14 p < 0.01 0.70 10 µs F (4 , 10) = 5.24 p = 0.02 0.53 100 µs F (2 , 12) = 3.79 p = 0.05 0.27 1 ms F (3 , 10) = 9.06 p < 0.01 0.63 10 ms F (4 , 13) = 4.15 p = 0.02 0.41
Differentiated HT22
ANOVA Significance Effect size (Ω2) 10 ns FW (3 , 11.76) = 13.41 p < 0.01 0.60 550 ns F (2 , 10) = 5.20 p = 0.03 0.39 1 µs F (2 , 16) = 4.56 p = 0.03 0.29 10 µs F (6 , 21) = 3.97 p < 0.01 0.39 100 µs F (4 , 16) = 6.13 p < 0.01 0.49 1 ms F (3 , 19) = 8.80 p < 0.01 0.50 10 ms F (4 , 20) = 6.02 p < 0.01 0.45
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Table S2 - Additional statistical parameters from the strength-duration curve.
All electric fields that were tested for threshold determination are provided by cell line,
including the sample size for each.
Cell type CHO U-87 HT22 undiff HT22 diff
Control 7 11 7 8
10 ns 22 kV/m 5 16.5 kV/m 4 22 kV/m 6 44 kV/m 8
34 kV/m 3 22.0 kV/m 4 34 kV/m 4 52 kV/m 6
44 kV/m 6 34.0 kV/m 4 44 kV/m 2 76 kV/m 5
44.0 kV/m 4
550 ns 1.6 kV/cm 4 1.2 kV/cm 3 1.6 kV/cm 4 2.0 kV/cm 3
2.0 kV/cm 4 1.6 kV/cm 2 2.0 kV/cm 5 4.5 kV/cm 2
2.4 kV/cm 4 2.0 kV/cm 3
1 µs 1.0 kV/cm 4 1.0 kV/cm 3 1.0 kV/cm 4 4.5 kV/cm 2
1.2 kV/cm 4 1.2 kV/cm 3 1.2 kV/cm 3 10. kV/cm 4
1.4 kV/cm 4 1.4 kV/cm 3 1.4 kV/cm 3
10 µs 0.30 kV/cm 3 0.35 kV/m 5 0.35 kV/m 3 0.60 kV/m 3
0.45 kV/cm 4 0.45 kV/m 6 0.45 kV/m 3 0.80 kV/m 3
0.60 kV/cm 4 0.60 kV/m 4 0.60 kV/m 3 1.20 kV/m 3
0.75 kV/m 5 0.75 kV/m 3 1.60 kV/m 4
1.80 kV/m 4
2.00 kV/m 3
100 µs 0.10 kV/cm 4 0.25 kV/m 3 0.50 kV/m 3 0.35 kV/cm 3
0.20 kV/cm 4 0.35 kV/m 6 0.75 kV/m 5 0.45 kV/cm 3
0.30 kV/cm 4 0.45 kV/m 5 0.75 kV/cm 3
0.40 kV/cm 4 1.00 kV/cm 6
1 ms 0.10 kV/cm 4 0.10 kV/cm 3 0.25 kV/cm 4 0.40 kV/cm 4
0.15 kV/cm 4 0.20 kV/cm 4 0.30 kV/cm 4 0.50 kV/cm 5
0.20 kV/cm 4 0.30 kV/cm 4 0.35 kV/cm 3 0.60 kV/cm 6
0.60 kV/cm 4
10 ms 0.02 kV/cm 3 0.04 kV/cm 4 0.24 kV/cm 3 0.20 kV/cm 4
0.06 kV/cm 3 0.08 kV/cm 4 0.28 kV/cm 3 0.24 kV/cm 3
0.10 kV/cm 3 0.12 kV/cm 4 0.32 kV/cm 3 0.28 kV/cm 6
0.40 kV/cm 2 0.36 kV/cm 4
108
Chapter 5 –
Discussion and Conclusion
109
5.1 Summary
This thesis investigated the effects of pulsed electric fields on multiple cell lines. Three
chapters evaluated important questions regarding cell membrane – electric field interactions.
The first experimental chapter compared the traditional view of this interaction with
experimental results using a statistical approach. The next chapter studied the role of
transmembrane proteins in PEF effects. These proteins, or ion channels, are often overlooked
in PEF research and are critically important to a cells response to environmental stimuli.
Finally, the last chapter investigated the electric field thresholds required to depolarize the
transmembrane potential and permeabilize the plasma membrane in multiple cell lines.
Several pulse durations, ranging from 10 ns to 10 ms were used. The results from each chapter
will be discussed as they pertain to the literature.
5.2 A comparative analysis of the theoretical and experimental
interactions of PEF with cells in vitro
The effects of pulsed electric fields on biological systems has been studied for more
than a half of a century. As with any scientific inquiry, a model was required to help understand
how these fields interact with cells. But what happens when the model fails to provide a true
representation of the effects we are interested in measuring?
The results from this section indicate that the fundamental mathematical models that
were intended to help guide us in designing and interpreting experiments have very low
predictive power. Specifically, when considering size, shape, orientation to the electric field,
and density of cells exposed, the currently accepted models account for less than 5 % of the
changes observed. It is important to mention that this chapter looked at the induced
transmembrane potential as the outcome variable.
Transmembrane potential was selected because the literature states that this is the
gateway to modulating cellular activity with applied electric fields. Both older and newer
110
literature have stated that an induced transmembrane voltage of ~ 1V is required to cause
breakdown of the cell membrane [17, 18, 34, 84, 230–234]
Cell have mechanisms by which they cope with induced transmembrane voltage under
physiological conditions. Transmembrane proteins, or ion channels, control the induced
voltage through opening and closing of these proteins. These channels, although studied
mostly in excitable cells, are present to a certain degree in all cells. They are responsible for
many cell processes from cell volume regulation, DNA replication and cell division [96, 235].
5.3 Nanosecond pulsed electric fields depolarize
transmembrane potential via voltage-gated K+, Ca2+ and
TRPM8 channels in U87 glioblastoma cells
The purpose of this section was to look at electric field - cell interactions with the
following question in mind: What if the changes in transmembrane potential following a single
10 nanosecond pulsed electric field were not due to electroporation of the plasma membrane?
As we saw in the previous section, there appears to be a fundamental flaw with the description
provided by the traditional theoretical model. This is most likely due to an oversimplification
of a cell, which is not merely a leaky dielectric membrane separating two conductive solutions.
A cell is a complex, living organism that is always adapting to its environment. As a result,
modelling the cell in the traditional way has very little predictive power when analyzing
experimental results.
Since we were working with applied voltage, it seemed most logical to study cellular
mechanisms which were responsible for regulating transmembrane potential. To accomplish
this task a series of pharmacological ion channel modulators were employed to monitor their
effects on membrane depolarization following nsPEF exposure. The underlying hypothesis
supposed that if the observed change in membrane potential was due to simple diffusion of
111
ions across the electroporated plasma membrane, then we should expect no significant effect
from chemical blockers or activators of ion channels.
Although few articles have explored the possibility of PEF influencing ion channel
behavior, our results appear to be consistent with the literature. Specifically, calcium influx
was abolished following PEF exposure of bovine chromaffin cells [64], as well as GH3 and
NG108 cells [63] when specific voltage-gated calcium channel blockers were used. In the latter
study, CHO cells were used as a negative control due to the lack of voltage-gated calcium
channels. When PEF was combined with or without calcium channel blockers, no increase in
intracellular calcium was observed.
In our study we have implicated additional channels, such as voltage-gated K+ channels
and TRPM8 channels, in the depolarization response following nsPEF exposure. Although
TRPM8 channels were originally described as cold-receptors, more recently they have been
shown to display voltage sensitivity [236–238]. We had to explore the possibility that TRPM8
involvement may have been an artefact because experimentation took place at ambient
temperature. To rule this out, experiments were replicated at 37°C and similar results were
observed.
Of course the presence of voltage-gated channels will differ significantly between cell
types and possibly within the same cell type. These differences could prove to be important
when designing in vivo experiments. As an example, in certain cases electrochemotherapy
could be refined to maximize effects on a given target cell type while minimizing effects on
surrounding tissues by exploiting these differences. The following chapter has been dedicated
to investigating these effects among various cell types and pulse durations.
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5.4 Plasma membrane depolarization and permeabilization
due to electric pulses in cell lines of different excitability
More than 20 years ago the first clinical trial used electroporation as a means to
significantly enhance chemotherapeutic uptake into tumors [239]. Since then, the study of
electrochemotherapy has continued to gain traction in the scientific and medical community.
Whether studies have utilized chemotherapeutics, high concentrations of extracellular
calcium or electric fields alone, PEF have shown to be an effective alternative to traditional
chemotherapy [40, 52, 66, 102, 182, 240, 241].
Treatment of malignant tissues with PEF has shown several significant advantages
over conventional treatments. One such advantage consists of chemical delivery directly into
the tumor. Chemotherapy is generally delivered intravenously in significant concentrations
which ultimately circulate through the entire body. Since these are highly toxic compounds,
serious secondary effects can often be expected. With electrochemotherapy,
chemotherapeutics can be injected locally to into the target tissues, and subsequent
application of PEF protocol permeabilizes the target and leads to enhanced uptake of the drug
[50, 51] while minimizing secondary effects associated with systemic administration.
Another advantage comes in the selectivity of the treatment. Whereas chemotherapy
is toxic to all cells, PEFs appear to have a greater effect on malignant cells than normal cells
[220]. Although not very well understood, this difference in sensitivity may be linked to
membrane repair. When comparing dye uptake following the standard ECT protocol and
viability 24 hours later, cancerous cell lines have been shown to be significantly more
vulnerable than normal primary cell lines [221].
Despite the advantages, one of the primary drawbacks with PEF treatment is the
potential for pain. This is due to nervous and muscular tissues in areas adjacent to the
treatment site which have become electrically excited from the applied electric field [212, 213].
The purpose of this section was to investigate PEF-induced permeability and excitation of
113
various cell lines. An important advance in PEF treatment would involve finding the
appropriate electric field duration and intensity that would minimize the excitation of
surrounding nervous tissue yet remain effective at permeabilizing the target cells.
Four cells lines were used for these experiments, three of which were non-excitable
under physiologic conditions, the other being terminally differentiated neurons. For each cell
line, PMPI was used to measure changes in membrane potential, and YO-PRO was used as a
measure of membrane permeability.
Consistent with the literature, we found that the electric field intensity required to
depolarize the transmembrane potential decreased as the pulse durations increased [25, 242,
243]. We also found that the electric field required to depolarize cells was significantly greater
in the differentiated neurons than the non-excitable cells. When we combine these results with
the fact that no difference in thresholds were observed for membrane permeability, we find
that by carefully selecting a treatment protocol with the appropriate intensity, it is possible to
achieve clinically relevant enhancement of chemical uptake while minimizing or preventing
the pain associated with excitation of the surrounding nervous tissues.
5.5 Conclusion
This thesis focused heavily on understanding the role of transmembrane ion channels
in pulsed electric field effects. These have been shown to be directly influenced in several
studies [63–65, 93]. In the first section we compared theoretical parameters influencing
membrane-electric field interactions with experimental results. We found that less than 5 %
of the experimental results could be attributed to factors included in current electro-physical
model, such as size, shape, orientation with respect to the electric field and the density of cells.
These results suggested, at least for long-lasting changes that were measured here, were
mediated to a large extent by other parameters.
114
One of those parameters are voltage-gated ion channels, which was the focus of the
second chapter. These are channels that are integral for many physiological processes and are
present, to varying degrees, in every type of cell. Although it is important that future
experiments look to understand the precise mechanism, it is no surprise that applying an
electric field would somehow influence the activity of electric field sensors in a cell. In addition
to directly acting on these channels, other research has suggested they may be damaged by
PEF exposure [224, 244, 245].
It was interesting that no ion channel blocker was able to completely abolish the
depolarizing response. It is important to consider the possibility that pores were formed in the
plasma membrane which allowed the diffusion of ions, and it was this diffusion that resulted
in the transmembrane potential being sufficiently depolarized to allow voltage-gated channels
to open. Whether or not the PEF acted directly or indirectly on the ion channels is something
that needs to be explored in the future; however, it is clear that they play a significant role in
the change in transmembrane potential following PEF exposure.
In the final experimental chapter we extended these results to include multiple cell
lines. A series of experiments looking at pulse durations from 10 ns to 10 ms were conducted
with membrane potential and membrane permeability as outcome variables. Multiple electric
field intensities were used for each duration in order to find the minimum fields strength
required to either depolarize, or permeabilize the plasma membrane. One of the most common
complaint reported from patients treated with PEF treatments is the pain associated with
repeated electrical stimulation. It would be beneficial to find a protocol which could limit or
prevent the pain associated with treatment.
Since the experienced pain is due to electrically exciting nervous tissue surrounding
the treatment site, we aimed to explore the possibility of preventing excitation without
interfering with the permeability required for enhanced drug uptake in electrochemotherapy.
Our results demonstrated that the threshold required for membrane depolarization was
115
different between cell lines. Specifically, the differentiated neurons required a significantly
greater field strength than the non-excitable cell.
In the second series of experiments investigating the threshold for
electropermeabilization in the same cells, we found that there were no significant difference
between field strengths required. This effect was consistent at every pulse duration tested.
These results are promising as they suggest it may be possible to find an electric field intensity
that would be able to enhance drug uptake, all the while avoiding excitation of the surrounding
nervous tissue associated with the sensation of pain. Most likely this effect would differ based
on several factors such as cell type, treatment site, or density of nervous tissue in the area.
Future research should focus on testing how well in vitro excitability correlates with in
vivo perception of pain. Potentially, this could reduce or eliminate the requirement for
sedatives and muscle relaxants in PEF treatments.
5.6 Perspectives
In the first experimental chapter we uncovered two significantly different populations
of U87 cells. This came in spite of the care taken to keep as many variables constant as possible,
including temperature, imaging medium, electric field intensity etc. Although there was not
enough time to experimentally pursue these differences further, these results require more
investigation. There were many interesting coincidences which may implicate cell cycle as a
target for future experimentation.
This is not something that has received a lot of attention in this field of study; however,
one study did report significant differences in PEF effects depending on the phase of cell cycle
[89]. Of course, during my last month as a Ph.D. student, an incredible tool arrived in our lab.
A Digital holographic microscope capable of monitoring cells long-term in 3D without the
need for fluorescent molecules. I truly hope future researchers will use this tool to investigate
the role of cell cycle.
116
In the second experimental chapter, we showed that by delivering a single 10 nsPEF
every 2.5 minutes, the membrane potential could not be recovered. This could be important
since cells oscillate between periods of depolarization and hyperpolarization that are
associated with DNA replication and division. If cells need to hyperpolarize to replicate their
DNA, maintaining a depolarized transmembrane potential over time could prove to be a novel
treatment for cancer that would require no chemotherapeutics and would not damage
surrounding tissues. Whether or not this is the case, I look forward to reading future results
investigating this question.
117
References
1. Barba FJ, Parniakov O, Pereira SA, et al (2015) Current applications and new
opportunities for the use of pulsed electric fields in food science and industry. Food
Res Int 77:773–798. doi: 10.1016/j.foodres.2015.09.015
2. Xue D, Farid MM (2015) Pulsed electric field extraction of valuable compounds from
white button mushroom (Agaricus bisporus). Innov Food Sci Emerg Technol 29:178–
186. doi: 10.1016/j.ifset.2015.03.012
3. Yang N, Huang K, Lyu C, Wang J (2016) Pulsed electric field technology in the
manufacturing processes of wine, beer, and rice wine: A review. Food Control 61:28–
38. doi: 10.1016/j.foodcont.2015.09.022
4. Lin L, Yahong M, Jinghui G, et al (2013) Effects of AC electric fields on the
cryopreservation of SD rat liver tissues. Annu Rep - Conf Electr Insul Dielectr
Phenomena, CEIDP 555–558. doi: 10.1109/CEIDP.2013.6748328
5. Dovgan B, Barlič A, Knežević M, Miklavčič D (2016) Cryopreservation of Human
Adipose-Derived Stem Cells in Combination with Trehalose and Reversible
Electroporation. J Membr Biol. doi: 10.1007/978-981-287-817-5
6. Dovgan B, Dermol J, Barlič A, et al (2016) Cryopreservation of Human Umbilical Stem
Cells in Combination with Trehalose and Reversible Electroporation. In: Jarm T,
Kramar P (eds) 1st World Congr. Electroporation Pulsed Electr. Fields Biol. Med.
Food {&} Environ. Technol. Portoro{ž}, Slov. Sept. 6 --10, 2015. Springer Singapore,
Singapore, pp 307–310
7. Cemazar M, Sersa G (2007) Electrotransfer of therapeutic molecules into tissues. Curr
Opin Mol Ther 9:554–562.
8. Pucihar G, Kotnik T, Miklavcic D, Teissie J (2008) Kinetics of transmembrane
transport of small molecules into electropermeabilized cells. Biophys J 95:2837–
2848. doi: 10.1529/biophysj.108.135541
118
9. Calvet CY, Thalmensi J, Liard C, et al (2014) Optimization of a gene electrotransfer
procedure for efficient intradermal immunization with an hTERT-based DNA vaccine
in mice. Mol Ther Methods Clin Dev 1:14045. doi: 10.1038/mtm.2014.45
10. Chopinet L, Batista-Napotnik T, Montigny A, et al (2013) Nanosecond electric pulse
effects on gene expression. J Membr Biol 246:851–859. doi: 10.1007/s00232-013-
9579-y
11. Pakhomova ON, Gregory BW, Semenov I, Pakhomov AG (2013) Two Modes of Cell
Death Caused by Exposure to Nanosecond Pulsed Electric Field. PLoS One. doi:
10.1371/journal.pone.0070278
12. Beebe SJ, Sain NM, Ren W (2013) Induction of Cell Death Mechanisms and Apoptosis
by Nanosecond Pulsed Electric Fields (nsPEFs). Cells 2:136–62. doi:
10.3390/cells2010136
13. Rubinsky B, Onik G, Mikus P (2007) Irreversible electroporation: A new ablation
modality - Clinical implications. Technol Cancer Res Treat 6:37–48. doi:
10.1177/153303460700600106
14. Meer G Van, Voelker DR, Feigenson GW (2008) Membrane lipids : where they are
and how they behave. Nat Rev Mol cell Biol 9:112–124. doi: 10.1038/nrm2330
15. Alberts B, Johnson A, Lewis J, et al (2002) Molecular biology of the cell, 4th ed.
Garland Science
16. Tortora G, Derrickson B (2008) Principles of anatomy and physiology, 12th ed. Wiley
17. Teissie J, Golzio M, Rols MP (2005) Mechanisms of cell membrane
electropermeabilization: A minireview of our present (lack of ?) knowledge. Biochim
Biophys Acta - Gen Subj 1724:270–280. doi: 10.1016/j.bbagen.2005.05.006
18. Rems L, Miklavcic D (2016) Tutorial: Electroporation of cells in complex materials
and tissue. J Appl Phys. doi: 10.1063/1.4949264
119
19. Gurtovenko AA, Vattulainen I (2005) Pore Formation Coupled to Ion Transport
through Lipid Membranes as Induced by Transmembrane Ionic Charge Imbalance :
Atomistic Molecular Dynamics Study. J Am Chem Soc 127:17570–17571.
20. Tarek M (2005) Membrane Electroporation: A Molecular Dynamics Simulation.
Biophys J 88:4045–4053. doi: 10.1529/biophysj.104.050617
21. Tieleman DP (2004) The molecular basis of electroporation. BMC Biochem 5:10. doi:
10.1186/1471-2091-5-10
22. Jianfei WJW, Yan MYM, Chenguo YCY, Chengxiang LCL (2008) A Review on
Molecular Dynamics Simulation for Biological Effects of Pulsed Electric Field. 2008
Int Conf High Volt Eng Appl 763–766. doi: 10.1109/ICHVE.2008.4774046
23. Vernier PT, Ziegler MJ (2007) Nanosecond Field Alignment of Head Group and Water
Dipoles in Electroporating Phospholipid Bilayers. J Phys Chem 111:12993–12996.
24. Sözer EB, Levine ZA, Vernier PT (2017) Quantitative Limits on Small Molecule
Transport via the Electropermeome — Measuring and Modeling Single Nanosecond
Perturbations. Sci Rep 7:57. doi: 10.1038/s41598-017-00092-0
25. Rogers WR, Merritt JH, Comeaux JA, et al (2004) Strength-duration curve an
electrically excitable tissue extended down to near 1 nanosecond. IEEE Trans Plasma
Sci 32:1587–1599. doi: 10.1109/TPS.2004.831758
26. Romeo S, Wu YH, Levine Z a., et al (2013) Water influx and cell swelling after
nanosecond electropermeabilization. Biochim Biophys Acta - Biomembr 1828:1715–
1722. doi: 10.1016/j.bbamem.2013.03.007
27. Carr L, Bardet SM, Burke RC, et al (2017) Calcium-independent disruption of
microtubule dynamics by nanosecond pulsed electric fields in U87 human
glioblastoma cells. Sci Rep. doi: 10.1038/srep41267
28. Kotnik T, Mir LM, Flisar K, et al (2001) Cell membrane electropermeabilization by
120
symmetrical bipolar rectangular pulses: Part I. Increased efficiency of
permeabilization. Bioelectrochemistry 54:83–90.
29. Pakhomov AG, Semenov I, Xiao S, et al (2014) Cancellation of cellular responses to
nanoelectroporation by reversing the stimulus polarity. Cell Mol Life Sci 71:4431–
4441. doi: 10.1007/s00018-014-1626-z
30. Schoenbach KH, Pakhomov AG, Semenov I, et al (2014) Ion transport into cells
exposed to monopolar and bipolar nanosecond pulses. Bioelectrochemistry. doi:
10.1016/j.bioelechem.2014.08.015
31. Ibey BL, Ullery J, Pakhomova ON, et al (2014) Bipolar nanosecond electric pulses are
less efficient at electropermeabilization and killing cells than monopolar pulses.
Biochem Biophys Res Commun 443:568–573. doi:
10.1016/j.bbrc.2013.12.004.Bipolar
32. Gowrishankar TR, Weaver JC (2006) Electrical behavior and pore accumulation in a
multicellular model for conventional and supra-electroporation. Biochem Biophys Res
Commun 349:643–653. doi: 10.1016/j.bbrc.2006.08.097
33. Tekle E, Oubrahim H, Dzekunov SM, et al (2005) Selective Field Effects on
Intracellular Vacuoles and Vesicle Membranes with Nanosecond Electric Pulses.
Biophys J 89:274–284. doi: 10.1529/biophysj.104.054494
34. Schwan HP (1988) Biological effects of non-ionizing radiations: Cellular properties
and interactions. Ann Biomed Eng 16:245–263. doi: 10.1007/BF02368002
35. Dev SB, Rabussay DP, Widera G, Hofmann GA (2000) Medical Applications of
Electroporation. IEEE Trans plasma Sci 28:206–223.
36. Vandermeulen G, Richiardi H, Escriou V, et al (2009) Skin-specific promoters for
genetic immunisation by DNA electroporation. Vaccine 27:4272–4277. doi:
10.1016/j.vaccine.2009.05.022
121
37. Heller R, Cruz Y, Heller LC, et al (2010) Electrically Mediated Delivery of Plasmid
DNA to the Skin, Using a Multielectrode Array. Hum Gene Ther 21:357–362. doi:
10.1089/hum.2009.065
38. Teissié J (2013) Electrically Mediated Gene Delivery: Basic and Translational
Concepts. Nov Gene Ther Approaches. doi: 10.5772/54780
39. Gothelf A, Gehl J (2010) Gene electrotransfer to skin; review of existing literature and
clinical perspectives. Curr Gene Ther 10:287–299. doi: 10.2174/156652310791823443
40. Gothelf A, Mir LM, Gehl J (2003) Electrochemotherapy : results of cancer treatment
using enhanced delivery of bleomycin by electroporation. Cancer Treat Rev 29:371–
387. doi: 10.1016/S0305-7372(03)00073-2
41. Breton M, Mir LM (2012) Microsecond and nanosecond electric pulses in cancer
treatments. Bioelectromagnetics 33:106–123. doi: 10.1002/bem.20692
42. Davalos R V., Mir LM, Rubinsky B (2005) Tissue Ablation with Irreversible
Electroporation. Ann Biomed Eng 33:223–231. doi: 10.1007/s10439-005-8981-8
43. Ting F, Tran M, Böhm M, et al (2016) Focal irreversible electroporation for prostate
cancer: functional outcomes and short-term oncological control. Prostate Cancer
Prostatic Dis 19:46–52. doi: 10.1038/pcan.2015.47
44. Rossmeisl JH, Garcia PA, Pancotto TE, et al (2015) Safety and feasibility of the
NanoKnife system for irreversible electroporation ablative treatment of canine
spontaneous intracranial gliomas. J Neurosurg 123:1008–1025. doi:
10.3171/2014.12.JNS141768
45. Jiang C, Davalos R V., Bischof JC (2015) A Review of Basic to Clinical Studies of
Irreversible Electroporation Therapy. IEEE Trans Biomed Eng 62:4–20. doi:
10.1109/TBME.2014.2367543
46. Scheffer HJ, Nielsen K, de Jong MC, et al (2014) Irreversible Electroporation for
122
Nonthermal Tumor Ablation in the Clinical Setting: A Systematic Review of Safety and
Efficacy. J Vasc Interv Radiol 1–15. doi: 10.1016/j.jvir.2014.01.028
47. Fruhling P, Nilsson A, Duraj F, et al (2017) Single-center nonrandomized clinical trial
to assess the safety and efficacy of irreversible electroporation ( IRE ) ablation of liver
tumors in humans : Short to mid-term results. Eur J Surg Oncol 1–7. doi:
10.1016/j.ejso.2016.12.004
48. Heller R, Heller LC (2015) Gene Electrotransfer Clinical Trials. In: Adv. Genet.
Elsevier, pp 235–262
49. Orlowski S, Belehradek JJ, Paoletti C, Mir L (1988) Transient electropermeabilization
of cells in culture. Increase of the cytotoxicity of anticancer drugs. Biochem Pharmacol
37:4727–4733.
50. Horiuchi A, Nikaido T, Mitsushita J, et al (2000) Enhancement of antitumor effect of
bleomycin by low-voltage in vivo electroporation- a study of human uterine
leiomyosarcomas in nude mice. Int J cancer J 88:640–644.
51. Gehl J, Skovsgaard T, Mir LM (1998) Enhancement of cytotoxicity by
electropermeabilization: an improved method for screening drugs. Anticancer drugs
9:319–325.
52. Falk H, Lambaa S, Johannesen HH, et al (2017) Electrochemotherapy and calcium
electroporation inducing a systemic immune response with local and distant
remission of tumors in a patient with malignant melanoma – a case report. Acta Oncol
(Madr). doi: 10.1080/0284186X.2017.1290274
53. Beebe SJ, Chen YJ, Sain NM, et al (2012) Transient Features in Nanosecond Pulsed
Electric Fields Differentially Modulate Mitochondria and Viability. PLoS One. doi:
10.1371/journal.pone.0051349
54. Ren W, Beebe SJ (2011) An apoptosis targeted stimulus with nanosecond pulsed
123
electric fields (nsPEFs) in E4 squamous cell carcinoma. Apoptosis 16:382–393. doi:
10.1007/s10495-010-0572-y
55. Beebe SJ, Fox PM, Rec LJ, et al (2002) Nanosecond Pulsed Electric Field ( nsPEF )
Effects on Cells and Tissues : Apoptosis Induction and Tumor Growth Inhibition.
IEEE Trans plasma Sci 30:286–292.
56. Vernier PT, Li A, Marcu L, et al (2003) Ultrashort Pulsed Electric Fields Induce
Membrane Phospholipid Translocation and Caspase Activation : Differential
Sensitivities of Jurkat T Lymphoblasts and Rat Glioma C6 Cells. IEEE Trans Dielectr
Electr Insul 10:795–809.
57. Chen N, Schoenbach KH, Kolb JF, et al (2004) Leukemic cell intracellular responses
to nanosecond electric fields. Biochem Biophys Res Commun 317:421–427. doi:
10.1016/j.bbrc.2004.03.063
58. Yin S, Chen X, Hu C, et al (2014) Nanosecond pulsed electric field (nsPEF) treatment
for hepatocellular carcinoma : A novel locoregional ablation decreasing lung
metastasis. Cancer Lett 346:285–291. doi: 10.1016/j.canlet.2014.01.009
59. Stacey M, Fox P, Buescher S, Kolb J (2011) Nanosecond pulsed electric field induced
cytoskeleton, nuclear membrane and telomere damage adversely impact cell survival.
Bioelectrochemistry 82:131–134. doi: 10.1016/j.bioelechem.2011.06.002
60. Silve A, Leray I, Mir LM (2012) Demonstration of cell membrane permeabilization to
medium-sized molecules caused by a single 10 ns electric pulse. Bioelectrochemistry
87:260–264. doi: 10.1016/j.bioelechem.2011.10.002
61. Breton M, Delemotte L, Silve A, et al (2012) Transport of siRNA through Lipid
Membranes Driven by Nanosecond Electric Pulses: An Experimental and
Computational Study. J Am Chem Soc 134:13938–13941.
62. Gowrishankar, Thiruvallur, R Esser AT, Vasilkoski Z, Smith KC, Weaver JC (2006)
124
Microdosimetry for conventional and supra-electroporation in cells with organelles.
Biochem Biophys Res Commun 341:1266–1276. doi: 10.1016/j.bbrc.2006.01.094
63. Semenov I, Xiao S, Kang D, et al (2015) Cell stimulation and calcium mobilization by
picosecond electric pulses. Bioelectrochemistry 105:65–71. doi:
10.1016/j.bioelechem.2015.05.013
64. Craviso GL, Choe S, Chatterjee P, et al (2010) Nanosecond electric pulses: A novel
stimulus for triggering Ca2+ influx into chromaffin cells via voltage-gated Ca2+
channels. Cell Mol Neurobiol 30:1259–1265. doi: 10.1007/s10571-010-9573-1
65. Pakhomov AG, Semenov I, Casciola M, Xiao S (2017) Neuronal excitation and
permeabilization by 200-ns pulsed electric field: An optical membrane potential study
with FluoVolt dye. BBA - Biomembr. doi: 10.1016/j.bbamem.2017.04.016
66. Nuccitelli R, Wood R, Kreis M, et al (2014) First-in-human trial of
nanoelectroablation therapy for basal cell carcinoma : proof of method. Exp Dermatol
23:130–142. doi: 10.1111/exd.12303
67. Miklavčič D (2017) Handbook of electroporation. Springer International Publishing
68. Mazères S, Sel D, Golzio M, et al (2009) Non invasive contact electrodes for in vivo
localized cutaneous electropulsation and associated drug and nucleic acid delivery. J
Control Release 134:125–131. doi: 10.1016/j.jconrel.2008.11.003
69. Vernier PT, Sun Y, Gundersen MA (2006) Nanoelectropulse-driven membrane
perturbation and small molecule permeabilization. BMC Cell Biol 7:1–16. doi:
10.1186/1471-2121-7-37
70. Jin L, Platisa J, Wooltorton JRA, et al (2012) Single action potentials and
subthreshold electrical events imaged in neurons with a novel fluorescent protein
voltage probe. Neuron 75:779–785. doi: 10.1016/j.neuron.2012.06.040.Single
71. Boyce FM, Bucher NLR (1996) Baculovirus-mediated transfer into mammalian cells.
125
Proc Natl Acad Sci 93:2348–2352.
72. Ghosh S, Parvez K, Banerjee K, et al (2002) Baculovirus as Mammalian Cell
Expression Vector for Gene Therapy : An Emerging Strategy. Mol Ther 6:5–11. doi:
10.1006/mthe.2000.0643
73. Kost TA, Condreat JP, Jarvis DL (2005) Baculovirus as versatile vectors for protein
expression in insect and mammalian cells. Nat Biotechnol 23:567–575. doi:
10.1038/nbt1095.Baculovirus
74. Scaduto RC, Grotyohann LW (1999) Measurement of mitochondrial membrane
potential using fluorescent rhodamine derivatives. Biophys J 76:469–477. doi:
10.1016/S0006-3495(99)77214-0
75. Solaini G, Sgarbi G, Lenaz G, Baracca A (2007) Evaluating Mitochondrial Membrane
Potential in Cells. Biosci Rep 27:11–21. doi: 10.1007/s10540-007-9033-4
76. Plfigek J, Sigler K (1996) Slow fluorescent indicators of membrane potential : a survey
of different approaches to probe response analysis. J Photochem Photobiol B Biol
33:101–124.
77. Nicholls DG (2006) Simultaneous monitoring of ionophore- and inhibitor-mediated
plasma and mitochondrial membrane potential changes in cultured neurons. J Biol
Chem 281:14864–74. doi: 10.1074/jbc.M510916200
78. Spitzner M, Ousingsawat J, Scheidt K, et al (2007) Voltage-gated K+ channels support
proliferation of colonic carcinoma cells. FASEB J 21:35–44. doi: 10.1096/fj.06-
6200com
79. Whiteaker KL, Gopalakrishnan SM, Groebe D, et al (2001) Validation of FLIPR
membrane potential dye for high throughput screening of potassium channel
modulators. J Biomol Screen 6:305–312. doi: 0803973233
80. Dorn A, Hermann F, Ebneth A, et al (2005) Evaluation of a High-Throughput
126
Fluorescence Assay Method for hERG Potassium Channel Inhibition. J Biomol Screen
10:339–347. doi: 10.1177/1087057104272045
81. Field A (2009) Discovering statistics using SPSS, 3rd ed. SAGE publications Ltd
82. Schwan HP (1957) Electrical properties of tissue and cell suspensions. Adv Biol Med
Phys 5:147–209.
83. Gabriel B, Teissie J (1999) Time Courses of Mammalian Cell Electropermeabilization
Observed by Millisecond Imaging of Membrane Property Changes during the Pulse.
Biophys J 76:2158–2165.
84. Frey W, White J a, Price RO, et al (2006) Plasma membrane voltage changes during
nanosecond pulsed electric field exposure. Biophys J 90:3608–3615. doi:
10.1529/biophysj.105.072777
85. Valic B, Golzio M, Pavlin M, et al (2003) Electric field induced trans-membrane
potential on spheroidal cell : theory and experiment. Eur Biophys J 32:519–528. doi:
10.1007/s00249-003-0296-9
86. Kotnik T, Pucihar G, Miklavcic D (2010) Induced Transmembrane Voltage and Its
Correlation with Electroporation-Mediated Molecular Transport. J Membr Biol
236:3–13. doi: 10.1007/s00232-010-9279-9
87. Carr L, Bardet SM, Arnaud-cormos D, et al (2018) Visualisation of an nsPEF induced
calcium wave using the genetically encoded calcium indicator GCaMP in U87 human
glioblastoma cells. Bioelectrochemistry 119:68–75. doi:
10.1016/j.bioelechem.2017.09.003
88. Puc M, Kotnik T, Mir LM, Miklavc D (2003) Quantitative model of small molecules
uptake after in vitro cell electropermeabilization. Bioelectrochemistry 60:1–10. doi:
10.1016/S1567-5394(03)00021-5
89. Hojo S, Shimizu K, Yositake H, et al (2003) The Relationship Between
127
Electropermeabilization and Cell Cycle and Cell Size of Saccharomyces Cerevisiae.
IEEE Trans Nanobioscience 2:35–39.
90. Sukhorukov VL, Djuzenova CS, Frank H, et al (1995) Electropermeabilization and
Fluorescent Tracer Exchange : The Role of Whole-Cell Capacitance. Cytometry
21:230–240.
91. Henslee BE, Morss A, Hu X, et al (2011) Electroporation Dependence on Cell Size :
Optical Tweezers Study. Anal Chem 83:3998–4003.
92. Denzi A, Camera F, Merla C, et al (2016) A Microdosimeric Study of Electropulsation
on Multiple Realistically Shaped Cells : Effect of Neighbours. J Membr Biol. doi:
10.1007/s00232-016-9912-3
93. Teissie J, Tsong TY (1980) Evidence of voltage-induced channel opening in Na/K
ATPase of human erythrocyte membrane. J Membr Biol 55:133–140. doi:
10.1007/BF01871155
94. Chen W, Lee RC (1994) Altered ion channel conductance and ionic selectivity induced
by large imposed membrane potential pulse. Biophys J 67:603–612. doi:
10.1016/S0006-3495(94)80520-X
95. Levin M (2007) Large-scale biophysics: ion flows and regeneration. Trends Cell Biol
17:261–270. doi: 10.1016/j.tcb.2007.04.007
96. Blackiston DJ, McLaughlin KA, Levin M (2009) Bioelectric controls of cell
proliferation: Ion channels, membrane voltage and the cell cycle. Cell Cycle 8:3519–
3528. doi: 10.1115/1.3071969.Automating
97. Rao VR, Perez-Neut M, Kaja S, Gentile S (2015) Voltage-gated ion channels in cancer
cell proliferation. Cancers (Basel) 7:849–875. doi: 10.3390/cancers7020813
98. Tay D, Bhathal P, Fox R (1991) Quantitation of Go and G1 Phase Cells in Primary
Carcinomas. J Clin Invest 87:519–527.
128
99. Motaln H, Koren A, Gruden K, et al (2015) Heterogeneous glioblastoma cell cross-talk
promotes phenotype alterations and enhanced drug resistance. Oncotarget 6:40998–
41017.
100. Burke RC, Bardet SM, Carr L, et al (2017) Nanosecond pulsed electric fields depolarize
transmembrane potential via voltage-gated K+, Ca2+ and TRPM8 channels in U87
glioblastoma cells. BBA - Biomembr 1859:2040–2050. doi:
10.1016/j.bbamem.2017.07.004
101. Esser AT, Smith KC, Gowrishankar TR, Weaver JC (2009) Towards Solid Tumor
Treatment by Nanosecond Pulsed Electric Fields. Technol cancer Res Treat 8:289–
306.
102. Nuccitelli R, Pliquett U, Chen X, et al (2006) Nanosecond pulsed electric fields cause
melanomas to self-destruct. Biochem Biophys Res Commun 343:351–360. doi:
10.1016/j.bbrc.2006.02.181
103. Guo S, Jackson DL, Burcus NI, et al (2014) Gene electrotransfer enhanced by
nanosecond pulsed electric fields. Mol Ther Methods Clin Dev 1:14043. doi:
10.1038/mtm.2014.43
104. SJ B, J W, PF B, et al (2003) Diverse effects of nanosecond pulsed electric fields on
cells and tissues. DNA Cell Biol 22:785–796.
105. Pakhomov AG, Kolb JF, White J a., et al (2007) Long-lasting plasma membrane
permeabilization in mammalian cells by nanosecond Pulsed Electric Field (nsPEF).
Bioelectromagnetics 28:655–663. doi: 10.1002/bem.20354
106. Cantu JC, Tarango M, Beier HT, Ibey BL (2016) The Biological Response Of Cells To
Nanosecond Pulsed Electric Fields Is Dependent On Plasma Membrane Cholesterol.
Biochim Biophys Acta - Biomembr 1858:2636–2646. doi:
10.1016/j.bbamem.2016.07.006
129
107. Semenov I, Xiao S, Pakhomov AG (2013) Primary pathways of intracellular Ca(2+)
mobilization by nanosecond pulsed electric field. Biochim Biophys Acta 1828:981–9.
doi: 10.1016/j.bbamem.2012.11.032
108. Son RS, Smith KC, Gowrishankar TR, et al (2014) Basic Features of a Cell
Electroporation Model : Illustrative Behavior for Two Very Different Pulses. J Membr
Biol 247:1209–1228. doi: 10.1007/s00232-014-9699-z
109. Bardet SM, Carr L, Soueid M, et al (2016) Multiphoton imaging reveals that
nanosecond pulsed electric fields collapse tumor and normal vascular perfusion in
human glioblastoma xenografts. Sci Rep 6:1–11. doi: 10.1038/srep34443
110. Tokman M, Lee JH, Levine ZA, et al (2013) Electric Field-Driven Water Dipoles:
Nanoscale Architecture of Electroporation. PLoS One. doi:
10.1371/journal.pone.0061111
111. Bowman AM, Nesin OM, Pakhomova ON, Pakhomov AG (2010) Analysis of plasma
membrane integrity by fluorescent detection of Tl + uptake. J Membr Biol 236:15–26.
doi: 10.1007/s00232-010-9269-y
112. Pakhomov AG, Bowman AM, Ibey BL, et al (2009) Lipid Nanopores Can Form a
Stable, Ion Channel-Like Conduction Pathway in Cell Membrane. Biochem Biophys
Res Commun 385:181–186. doi: 10.1016/j.bbrc.2009.05.035.Lipid
113. Li M, Xiong ZG (2011) Ion channels as targets for cancer therapy. Int J Physiol
Pathophysiol Pharmacol 3:156–166. doi: 10.1115/1.4026364
114. Prevarskaya N, Skryma R, Shuba Y (2010) Ion channels and the hallmarks of cancer.
Trends Mol Med 16:107–121. doi: 10.1016/j.molmed.2010.01.005
115. Clark MJ, Homer N, O’Connor BD, et al (2010) U87MG decoded: The genomic
sequence of a cytogenetically aberrant human cancer cell line. PLoS Genet. doi:
10.1371/journal.pgen.1000832
130
116. Ducret T, Vacher A-M, Vacher P (2003) Voltage-dependent ionic conductances in the
human malignant astrocytoma cell line U87-MG. Mol Membr Biol 20:329–343. doi:
10.1080/0968763031000138037
117. Molenaar RJ (2011) Ion Channels in Glioblastoma. ISRN Neurol 2011:1–7. doi:
10.5402/2011/590249
118. Chin LS, Park CC, Zitnay KM, et al (1997) 4-Aminopyridine Causes Apoptosis and
Blocks an Outward Rectifier K + Channel in Malignant Astrocytoma Cell Lines. J
Neurosci Res 48:122–127.
119. Chattopadhyay N, Ye C-P, Yamaguchi T, et al (1999) Evidence for Extracellular
Calcium-Sensing Receptor Mediated Opening of an Outward K ؉ Channel in a Human
Astrocytoma Cell Line ( U87 ). Glia 26:64–72.
120. McFerrin MB, Sontheimer H (2006) A role for ion channels in glioma cell invasion.
Neuron Glia Biol 2:39–49. doi: 10.1017/S17440925X06000044
121. Arcangeli A, Crociani O, Lastraioli E, et al (2009) Targeting Ion Channels in Cancer :
A Novel Frontier in Antineoplastic Therapy. Curr Med Chem 16:66–93.
122. Delmas P, Gola M (1995) Choline blocks large conductance Kca channels in
mammalian sympathetic neurones. Neurosci Lett 189:109–112.
123. Lippiat JD, Standen NB, Davies NW (1998) Block of cloned BK(Ca) channels (rSlo)
expressed in HEK 293 cells by N-methyl D-glucamine. Pflugers Arch Eur J Physiol
436:810–812. doi: 10.1007/s004240050708
124. Wolff C, Fuks B, Chatelain P (2003) Comparative Study of Membrane Potential-
Sensitive Fluorescent Probes and their Use in Ion Channel Screening Assays. J Biomol
Screen 8:533–543. doi: 10.1177/1087057103257806
125. Goehring I, Gerencser AA, Schmidt S, et al (2012) Plasma membrane potential
oscillations in insulin secreting Ins-1 832/13 cells do not require glycolysis and are not
131
initiated by fluctuations in mitochondrial bioenergetics. J Biol Chem 287:15706–
15717. doi: 10.1074/jbc.M111.314567
126. Baxter DF, Kirk M, Garcia AF, et al (2002) A novel membrane potential-sensitive
fluorescent dye improves cell-based assays for ion channels. J Biomol Screen Off J
Soc Biomol Screen 7:79–85. doi: 10.1177/108705710200700110
127. Yan J, Aldrich RW (2010) LRRC26 auxiliary protein allows BK channel activation at
resting voltage without calcium. Nature 466:513–516. doi: 10.1038/nature09162
128. Warbington L, Hillman T, Adams C, Stern M (1996) Reduced transmitter release
conferred by mutations in the slowpoke-encoded Ca2+-activated K+ channel gene of
Drosophila. Invertebr Neurosci 2:51–60.
129. Pattillo JM, Yazejian B, Digregorio DA, et al (2001) Contribution of presynaptic
calcium-activated potassium currents to transmitter release regulation in cultured
xenopus nerve-muscle synapses. Neuroscience 102:229–240.
130. Skinner LJ, Enée V, Beurg M, et al (2003) Contribution of BK Ca2+ -Activated K+
Channels to Auditory Neurotransmission in the Guinea Pig Cochlea. J Neurophysiol
90:320–332.
131. Xu JW, Slaughter MM (2005) Large-Conductance Calcium-Activated Potassium
Channels Facilitate Transmitter Release in Salamander Rod Synapse. J Neurosci
25:7660–7668. doi: 10.1523/JNEUROSCI.1572-05.2005
132. Guéguinou M, Chantôme A, Fromont G, et al (2014) KCa and Ca2+ channels: The
complex thought. Biochim Biophys Acta 1843:2322–2333. doi:
10.1016/j.bbamcr.2014.02.019
133. Schütz GJ, Kada G, Pastushenko VP, Schindler H (2000) Properties of lipid
microdomains in a muscle cell membrane visualized by single molecule microscopy.
EMBO J 19:892–901. doi: 10.1093/emboj/19.5.892
132
134. Dart C (2010) Lipid microdomains and the regulation of ion channel function. J
Physiol 588:3169–78. doi: 10.1113/jphysiol.2010.191585
135. Gackière F, Warnier M, Katsogiannou M, et al (2013) Functional coupling between
large-conductance potassium channels and Cav3.2 voltage-dependent calcium
channels participates in prostate cancer cell growth. Biol Open 2:941–51. doi:
10.1242/bio.20135215
136. Grunnet M, Kaufmann WA (2004) Coassembly of big conductance Ca2+-activated K+
channels and L-type voltage-gated Ca2+ channels in rat brain. J Biol Chem
279:36445–36453. doi: 10.1074/jbc.M402254200
137. Wondergem R, Bartley JW (2009) Menthol increases human glioblastoma
intracellular Ca2+, BK channel activity and cell migration. J Biomed Sci 16:1–7. doi:
10.1186/1423-0127-16-90
138. Reinhart PH, Chung S, Levitan IB (1989) A family of calcium-dependent potassium
channels from rat brain. Neuron 2:1031–1041. doi: 0896-6273(89)90227-4 [pii]
139. Benton MD, Lewis AH, Bant JS, Raman IM (2013) Iberiotoxin-sensitive and -
insensitive BK currents in Purkinje neuron somata. J Neurophysiol 109:2528–41. doi:
10.1152/jn.00127.2012
140. Yu M, Liu S, Sun P, et al (2016) Peptide toxins and small-molecule blockers of BK
channels. Acta Pharmacol Sin 37:56–66. doi: 10.1038/aps.2015.139
141. Berkefeld H, Fakler B, Schulte UWE (2010) Ca 2+-Activated K+ Channels : From
Protein Complexes to Function. Physiol Rev 90:1437–1459. doi:
10.1152/physrev.00049.2009.
142. Wang B, Jaffe DB, Brenner R (2014) Current understanding of iberiotoxin-resistant
BK channels in the nervous system. Front Physiol 5:1–11. doi:
10.3389/fphys.2014.00382
133
143. Shruti S, Urban-Ciecko J, Fitzpatrick JA, et al (2012) The brain-specific beta4 subunit
downregulates BK channel cell surface expression. PLoS One. doi:
10.1371/journal.pone.0033429
144. Meera P, Wallner M, Toro L (2000) A neuronal beta subunit (KCNMB4) makes the
large conductance, voltage- and Ca2+-activated K+ channel resistant to charybdotoxin
and iberiotoxin. Proc Natl Acad Sci U S A 97:5562–7. doi: 10.1073/pnas.100118597
145. Liu X, Chang Y, Reinhart PH, et al (2002) Cloning and characterization of glioma BK,
a novel BK channel isoform highly expressed in human glioma cells. J Neurosci
22:1840–9. doi: 22/5/1840 [pii]
146. Marie C, Verkerke HP, Theodorescu D, Petri WA (2015) A whole-genome RNAi screen
uncovers a novel role for human potassium channels in cell killing by the parasite
Entamoeba histolytica. Sci Rep 5:1–18. doi: 10.1038/srep13613\rsrep13613 [pii]
147. Brelidze TI, Magleby KL (2004) Protons block BK channels by competitive inhibition
with K+ and contribute to the limits of unitary currents at high voltages. J Gen Physiol
123:305–19. doi: 10.1085/jgp.200308951
148. Peier AM, Moqrich A, Hergarden AC, et al (2002) A TRP Channel that Senses Cold
Stimuli and Menthol. Cell 108:705–715. doi: 10.1016/S0092-8674(02)00652-9
149. Chen J, Kim D, Bianchi BR, et al (2009) Pore dilation occurs in TRPA1 but not in
TRPM8 channels. Mol Pain 5:1–6. doi: 10.1186/1744-8069-5-3
150. Harteneck C (2005) Function and pharmacology of TRPM cation channels. Naunyn
Schmiedebergs Arch Pharmacol 371:307–314. doi: 10.1007/s00210-005-1034-x
151. Tominaga M, Caterina MJ (2004) Thermosensation and pain. J Neurobiol 61:3–12.
doi: 10.1002/neu.20079
152. Yoon J, Leblanc N, Zaklit J, et al (2016) Enhanced Monitoring of Nanosecond Electric
Pulse-Evoked Membrane Conductance Changes in Whole-Cell Patch Clamp
134
Experiments. J Membr Biol 249:1–12. doi: 10.1007/s00232-016-9902-5
153. Binshtok AM, Bean BP, Woolf CJ (2007) Inhibition of nociceptors by TRPV1-
mediated entry of impermeant sodium channel blockers. Nature 449:607–10. doi:
10.1038/nature06191
154. Banke TG, Chaplan SR, Wickenden a D (2010) Dynamic changes in the TRPA1
selectivity filter lead to progressive but reversible pore dilation. Am J Physiol Cell
Physiol 298:C1457-68. doi: 10.1152/ajpcell.00489.2009
155. Cao E, Liao M, Cheng Y, Julius D (2013) TRPV1 structures in distinct conformations
reveal mechanisms of activation. Nature 504:113–118. doi: 10.1038/nbt.3121.ChIP-
nexus
156. Chung M-K, Güler AD, Caterina MJ (2008) TRPV1 shows dynamic ionic selectivity
during agonist stimulation. Nat Neurosci 11:555–564. doi: 10.1038/nn.2102
157. Cui J, Yang H, Lee US (2009) Molecular Mechanisms of BK Channel Activation. Cell
Mol life Sci 66:852–875. doi: 10.1007/s00018-008-8609-x.Molecular
158. Ge L, Hoa NT, Wilson Z, et al (2014) Big Potassium (BK) ion channels in biology,
disease and possible targets for cancer immunotherapy. Int Immunopharmacol
22:427–443. doi: 10.1016/j.intimp.2014.06.040
159. Ge L, Hoa NT, Cornforth AN, et al (2012) Glioma big potassium channel expression in
human cancers and possible T cell epitopes for their immunotherapy. J Immunol
189:2625–2634. doi: 10.4049/jimmunol.1102965
160. Han X, Xi L, Wang H, et al (2008) The potassium ion channel opener NS1619 inhibits
proliferation and induces apoptosis in A2780 ovarian cancer cells. Biochem Biophys
Res Commun 375:205–209. doi: 10.1016/j.bbrc.2008.07.161
161. Cox DH, Cui J, Aldrich RW (1997) Allosteric gating of a large conductance Ca-
activated K+ channel. J Gen Physiol 110:257–281. doi: 10.1085/jgp.110.3.257
135
162. Zhao H, Sokabe M (2008) Tuning the mechanosensitivity of a BK channel by changing
the linker length. Cell Res 18:871–8. doi: 10.1038/cr.2008.88
163. Roth CC, Barnes R a, Ibey BL, et al (2015) Characterization of Pressure Transients
Generated by Nanosecond Electrical Pulse (nsEP) Exposure. Sci Rep 5:15063. doi:
10.1038/srep15063
164. Kotnik T, Kramar P, Pucihar G, et al (2012) Cell membrane electroporation- Part 1:
The phenomenon. IEEE Electr Insul Mag 28:14–23. doi: 10.1109/MEI.2012.6268438
165. Tsong TY (1991) Electroporation of cell membranes. Biophys J 60:297–306. doi:
10.1016/S0006-3495(91)82054-9
166. Weaver JC (1993) Electroporation: a general phenomenon for manipulating cells and
tissues. J Cell Biochem 51:426–435.
167. Kotnik T, Frey W, Sack M, et al (2015) Electroporation-based applications in
biotechnology. Trends Biotechnol. doi: 10.1016/j.tibtech.2015.06.002
168. Mahnič-Kalamiza S, Vorobiev E, Miklavčič D (2014) Electroporation in food
processing and biorefinery. J Membr Biol 247:1279–1304.
169. Toepfl S, Siemer C, Saldaña-Navarro G, Heinz V (2014) Overview of Pulsed Electric
Fields Processing for Food. In: Emerg. Technol. Food Process. Elsevier, pp 93–114
170. Yarmush ML, Golberg A, Serša G, et al (2014) Electroporation-Based Technologies for
Medicine: Principles, Applications, and Challenges. Annu Rev Biomed Eng 16:295–
320. doi: 10.1146/annurev-bioeng-071813-104622
171. Daud AI, DeConti RC, Andrews S, et al (2008) Phase I trial of interleukin-12 plasmid
electroporation in patients with metastatic melanoma. J Clin Oncol 26:5896–5903.
172. Calvet CY, André FM, Mir LM (2014) Dual therapeutic benefit of electroporation-
mediated DNA vaccination in vivo: Enhanced gene transfer and adjuvant activity.
Oncoimmunology 3:e28540. doi: 10.4161/onci.28540
136
173. Trimble CL, Morrow MP, Kraynyak KA, et al (2015) Safety, efficacy, and
immunogenicity of VGX-3100, a therapeutic synthetic DNA vaccine targeting human
papillomavirus 16 and 18 E6 and E7 proteins for cervical intraepithelial neoplasia 2/3:
a randomised, double-blind, placebo-controlled phase 2b trial. Lancet 386:2078–
2088. doi: 10.1016/S0140-6736(15)00239-1
174. Vasan S, Hurley A, Schlesinger SJ, et al (2011) In Vivo Electroporation Enhances the
Immunogenicity of an HIV-1 DNA Vaccine Candidate in Healthy Volunteers. PLoS
One 6:e19252. doi: 10.1371/journal.pone.0019252
175. Serša G, Teissié J, Čemažar M, et al (2015) Electrochemotherapy of tumors as in situ
vaccination boosted by immunogene electrotransfer. Cancer Immunol Immunother
64:1315–1327. doi: 10.1007/s00262-015-1724-2
176. Denet A-R, Vanbever R, Préat V (2004) Skin electroporation for transdermal and
topical delivery. Adv Drug Deliv Rev 56:659–674. doi: 10.1016/j.addr.2003.10.027
177. Zorec B, Préat V, Miklavčič D, Pavšelj N (2013) Active enhancement methods for
intra- and transdermal drug delivery: a review. Zdr Vestn 82:339–56.
178. Al-Sakere B, André F, Bernat C, et al (2007) Tumor Ablation with Irreversible
Electroporation. PLoS One 2:e1135. doi: 10.1371/journal.pone.0001135
179. Gasbarrini A, Campos WK, Campanacci L, Boriani S (2015) Electrochemotherapy to
Metastatic Spinal Melanoma: A Novel Treatment of Spinal Metastasis? Spine (Phila
Pa 1976) 40:E1340–E1346. doi: 10.1097/BRS.0000000000001125
180. Mali B, Jarm T, Snoj M, et al (2013) Antitumor effectiveness of electrochemo-therapy:
A systematic review and meta-analysis. Eur J Surg Oncol 39:4–16.
181. Miklavčič D, Mali B, Kos B, et al (2014) Electrochemotherapy: from the drawing board
into medical practice. Biomed Eng Online 13:29. doi: 10.1186/1475-925X-13-29
182. Bianchi G, Campanacci L, Ronchetti M, Donati D (2016) Electrochemotherapy in the
137
Treatment of Bone Metastases: A Phase II Trial. World J Surg 40:3088–3094. doi:
10.1007/s00268-016-3627-6
183. Hille B (1992) Ionic channels of excitable membranes, 2nd ed. Sinauer Associates,
Sunderland, Mass
184. Garcia PA, Rossmeisl JH, Robertson JL, et al (2012) 7.0-T Magnetic Resonance
Imaging Characterization of Acute Blood-Brain-Barrier Disruption Achieved with
Intracranial Irreversible Electroporation. PLoS One 7:e50482. doi:
10.1371/journal.pone.0050482
185. Garcia PA, Pancotto T, Rossmeisl JH, et al (2011) Non-thermal irreversible
electroporation (N-TIRE) and adjuvant fractionated radiotherapeutic multimodal
therapy for intracranial malignant glioma in a canine patient. Technol Cancer Res
Treat 10:73–83.
186. Hjouj M, Last D, Guez D, et al (2012) MRI Study on Reversible and Irreversible
Electroporation Induced Blood Brain Barrier Disruption. PLoS One 7:e42817. doi:
10.1371/journal.pone.0042817
187. Linnert M, Iversen HK, Gehl J (2012) Multiple brain metastases - current
management and perspectives for treatment with electrochemotherapy. Radiol Oncol.
doi: 10.2478/v10019-012-0042-y
188. Sharabi S, Kos B, Last D, et al (2016) A statistical model describing combined
irreversible electroporation and electroporation-induced blood-brain barrier
disruption. Radiol Oncol 50:28–38.
189. Neal RE, Millar JL, Kavnoudias H, et al (2014) In vivo characterization and numerical
simulation of prostate properties for non-thermal irreversible electroporation
ablation: Characterized and Simulated Prostate IRE. Prostate 74:458–468. doi:
10.1002/pros.22760
138
190. Tschon M, Salamanna F, Ronchetti M, et al (2015) Feasibility of Electroporation in
Bone and in the Surrounding Clinically Relevant Structures: A Preclinical
Investigation. Technol Cancer Res Treat. doi: 10.1177/1533034615604454
191. Lavee J, Onik G, Mikus P, Rubinsky B (2007) A Novel Nonthermal Energy Source for
Surgical Epicardial Atrial Ablation: Irreversible Electroporation. Heart Surg Forum
10:E162–E167. doi: 10.1532/HSF98.20061202
192. Neven K, van Driel V, van Wessel H, et al (2014) Myocardial Lesion Size After
Epicardial Electroporation Catheter Ablation After Subxiphoid Puncture. Circ
Arrhythmia Electrophysiol 7:728–733. doi: 10.1161/CIRCEP.114.001659
193. Xie F, Varghese F, Pakhomov AG, et al (2015) Ablation of Myocardial Tissue With
Nanosecond Pulsed Electric Fields. PLoS One 10:e0144833. doi:
10.1371/journal.pone.0144833
194. Gehl J, Sørensen TH, Nielsen K, et al (1999) In vivo electroporation of skeletal muscle:
threshold, efficacy and relation to electric field distribution. Biochim Biophys Acta -
Gen Subj 1428:233–240. doi: 10.1016/S0304-4165(99)00094-X
195. Satkauskas S, Bureau MF, Puc M, et al (2002) Mechanisms of in Vivo DNA
Electrotransfer: Respective Contributions of Cell Electropermeabilization and DNA
Electrophoresis. Mol Ther 5:133–140. doi: 10.1006/mthe.2002.0526
196. Ayuni EL, Gazdhar A, Giraud MN, et al (2010) In Vivo Electroporation Mediated Gene
Delivery to the Beating Heart. PLoS One 5:e14467. doi: 10.1371/journal.pone.0014467
197. Bulysheva AA, Hargrave B, Burcus N, et al (2016) Vascular endothelial growth factor-
A gene electrotransfer promotes angiogenesis in a porcine model of cardiac ischemia.
Gene Ther 23:649–656. doi: 10.1038/gt.2016.35
198. Li W, Fan Q, Ji Z, et al (2011) The Effects of Irreversible Electroporation (IRE) on
Nerves. PLoS One 6:e18831. doi: 10.1371/journal.pone.0018831
139
199. Onik G, Mikus P, Rubinsky B (2007) Irreversible electroporation: implications for
prostate ablation. Technol Cancer Res Treat 6:295–300.
200. Casciola M, Xiao S, Pakhomov AG (2017) Damage-free peripheral nerve stimulation
by 12-ns pulsed electric field. Sci Rep 7:10453. doi: 10.1038/s41598-017-10282-5
201. Schoellnast H, Monette S, Ezell PC, et al (2011) Acute and subacute effects of
irreversible electroporation on nerves: experimental study in a pig model. Radiology
260:421–427. doi: 10.1148/radiol.11103505
202. Nevian T, Helmchen F (2007) Calcium indicator loading of neurons using single-cell
electroporation. Pflügers Arch - Eur J Physiol 454:675–688. doi: 10.1007/s00424-
007-0234-2
203. van Driel VJHM, Neven K, van Wessel H, et al (2015) Low vulnerability of the right
phrenic nerve to electroporation ablation. Hear Rhythm 12:1838–1844. doi:
10.1016/j.hrthm.2015.05.012
204. Arena CB, Davalos R V. (2012) Advances in Therapeutic Electroporation to Mitigate
Muscle Contractions. J Membr Sci Technol. doi: 10.4172/2155-9589.1000e102
205. Golberg A, Rubinsky B (2012) Towards Electroporation Based Treatment Planning
Considering Electric Field Induced Muscle Contractions. Technol Cancer Res Treat
11:189–201. doi: 10.7785/tcrt.2012.500249
206. Miklavčič D, Pucihar G, Pavlovec M, et al (2005) The effect of high frequency electric
pulses on muscle contractions and antitumor efficiency in vivo for a potential use in
clinical electrochemotherapy. Bioelectrochemistry 65:121–128. doi:
10.1016/j.bioelechem.2004.07.004
207. Županič A, Ribarič S, Miklavčič D (2007) Increasing the repetition frequency of
electric pulse delivery reduces unpleasant sensations that occur in
electrochemotherapy. Neoplasma 54:246–250.
140
208. Ball C, Thomson KR, Kavnoudias H (2010) Irreversible Electroporation: A New
Challenge in “Out of Operating Theater” Anesthesia. Anesth Analg 110:1305–1309.
doi: 10.1213/ANE.0b013e3181d27b30
209. Deodhar A, Dickfeld T, Single GW, et al (2011) Irreversible electroporation near the
heart: ventricular arrhythmias can be prevented with ECG synchronization. AJR Am J
Roentgenol 196:W330-335. doi: 10.2214/AJR.10.4490
210. Mali B, Gorjup V, Edhemovic I, et al (2015) Electrochemotherapy of colorectal liver
metastases - an observational study of its effects on the electrocardiogram. Biomed
Eng Online 14:S5. doi: 10.1186/1475-925X-14-S3-S5
211. Mali B, Jarm T, Corovic S, et al (2008) The effect of electroporation pulses on
functioning of the heart. Med Biol Eng Comput 46:745–757. doi: 10.1007/s11517-008-
0346-7
212. Jiang N, Cooper BY (2011) Frequency-dependent interaction of ultrashort E-fields
with nociceptor membranes and proteins. Bioelectromagnetics 32:148–163. doi:
10.1002/bem.20620
213. Nene D, Jiang N, Rau KK, et al (2006) Nociceptor activation and damage by pulsed E-
fields. doi: 10.1117/12.665181
214. Spitzner M, Ousingsawat J, Scheidt K, et al (2006) Voltage-gated K+ channels support
proliferation of colonic carcinoma cells. FASEB J 21:35–44. doi: 10.1096/fj.06-
6200com
215. Wolff C, Fuks B, Chatelain P (2003) Comparative study of membrane potential-
sensitive fluorescent probes and their use in ion channel screening assays. J Biomol
Screen 8:533–543. doi: 10.1177/1087057103257806
216. Lalik PH, Krafte DS, Volberg WA, Ciccarelli RB (1993) Characterization of
endogenous sodium channel gene expressed in Chinese hamster ovary cells. Am J
141
Physiol Cell Physiol 264:C803-9.
217. Skryma R, Prevarskaya N, Vacher P, Dufy B (1994) Voltage-dependent Ca2+ channels
in Chinese hamster ovary (CHO) cells. FEBS 349:289–294.
218. Gamper N, Stockand JD, Shapiro MS (2005) The use of Chinese hamster ovary (CHO)
cells in the study of ion channels. J Pharmacol Toxicol Methods 51:177–185. doi:
10.1016/j.vascn.2004.08.008
219. Kandel ER, Schwartz JH, Jessell TM, et al (2012) Principles of neural science, 5th ed.
McGraw-Hill, Education
220. Frandsen SK, Kruger MB, Mangalanathan UM, et al (2017) Normal and Malignant
Cells Exhibit Differential Responses to Calcium Electroporation. Cancer Res 77:1–14.
doi: 10.1158/0008-5472.CAN-16-1611
221. Frandsen SK, McNeil AK, Novak I, et al (2016) Difference in Membrane Repair
Capacity Between Cancer Cell Lines and a Normal Cell Line. J Membr Biol 249:569–
576. doi: 10.1007/s00232-016-9910-5
222. Fairless R, Beck A, Kravchenko M, et al (2013) Membrane Potential Measurements of
Isolated Neurons Using a Voltage-Sensitive Dye. PLoS One 8:e58260. doi:
10.1371/journal.pone.0058260
223. Rols MP, Delteil C, Golzio M, Teissié J (1998) Control by ATP and ADP of voltage-
induced mammalian-cell-membrane permeabilization, gene transfer and resulting
expression. Eur J Biochem 254:382–388.
224. Chen W, Zhongsheng Z, Lee RC (2006) Supramembrane potential-induced
electroconformational changes in sodium channel proteins: A potential mechanism
involved in electric injury. Burns 32:52–59. doi: 10.1016/j.burns.2005.08.008
225. Levin M, Stevenson CG (2012) Regulation of Cell Behavior and Tissue Patterning by
Bioelectrical Signals: Challenges and Opportunities for Biomedical Engineering. Annu
142
Rev Biomed Eng 14:295–323. doi: 10.1146/annurev-bioeng-071811-150114
226. Dermol J, Miklavčič D (2014) Predicting electroporation of cells in an inhomogeneous
electric field based on mathematical modeling and experimental CHO-cell
permeabilization to propidium iodide determination. Bioelectrochemistry 100:52–61.
doi: 10.1016/j.bioelechem.2014.03.011
227. Pucihar G, Kotnik T, Teissié J, Miklavčič D (2007) Electropermeabilization of dense
cell suspensions. Eur Biophys J 36:172–185.
228. Susil R, Šemrov D, Miklavčič D (1998) Electric field induced transmembrane potential
depends on cell density and organization. Electro- and Magnetobiology 17:391–399.
229. Čemažar M, Jarm T, Miklavčič D, et al (1998) Effect of electric-field intensity on
electropermeabilization and electrosensitivity of various tumor-cell lines in vitro.
Electro- and Magnetobiology 17:263–272.
230. Moen EK, Ibey BL, Beier HT, Armani AM (2016) Quantifying pulsed electric field-
induced membrane nanoporation in single cells. Biochim Biophys Acta - Biomembr
1858:2795–2803. doi: 10.1016/j.bbamem.2016.08.007
231. Muller KJ, Sukhorukov VL, Zimmermann U (2001) Membrane Biology Reversible
Electropermeabilization of Mammalian Cells by High-Intensity , Ultra-Short. J
Membr Biol 184:161–170. doi: 10.1007/s00232-001-0084-3
232. Satkauskas S, Ruzgys P, Venslauskas MS (2012) Towards the mechanisms for efficient
gene transfer into cells and tissues by means of cell electroporation. Expert Opin Biol
Ther 12:275–286. doi: 10.1517/14712598.2012.654775
233. Kinosita KJ, Tsong TY (1977) Voltage-induced pore formation and hemolysis of
human erythrocytes. Biochim Biophys Acta 471:227–242.
234. Sale AJH, Hamilton WA (1968) Effects of high electric fields on micro-organisms: III.
Lysis of erythrocytes and protoplasts. Biochim Biophys Acta - Biomembr 163:37–43.
143
doi: 10.1016/0005-2736(68)90030-8
235. Yang M, Brackenbury WJ (2013) Membrane potential and cancer progression. Front
Physiol 4:1–10. doi: 10.3389/fphys.2013.00185
236. Voets T, Owsianik G, Janssens A, et al (2007) TRPM8 voltage sensor mutants reveal a
mechanism for integrating thermal and chemical stimuli. Nat Chem Biol 3:174–182.
doi: 10.1038/nchembio862
237. Fernández JA, Skryma R, Bidaux G, et al (2011) Voltage- and cold-dependent gating of
single TRPM8 ion channels. J Gen Physiol 137:173–195. doi: 10.1085/jgp.201010498
238. Raddatz N, Castillo JP, Gonzalez C, et al (2014) Temperature and Voltage Coupling to
Channel Opening in Transient Receptor Potential Melastatin 8 ( TRPM8 ) *. J Biol
Chem 289:35438–35454. doi: 10.1074/jbc.M114.612713
239. Belehradek M, Domenge C, Luboinski B, et al (1993) Electrochemotherapy , a New
Antitumor Treatment First Clinical Phase I-II Trial. Cancer 72:3694–3700.
240. Falk H, Matthiessen LW, Wooler G, Gehl J (2017) Calcium electroporation for
treatment of cutaneous metastases ; a randomized double- blinded phase II study ,
comparing the effect of calcium electroporation with electrochemotherapy. Acta Oncol
(Madr) 1–9. doi: 10.1080/0284186X.2017.1355109
241. Gehl J, Geertsen PF (2000) Efficient palliation of haemorrhaging malignant
melanoma skin metastases by electrochemotherapy. Melanoma Res 10:585–589.
242. Boinagrov D, Loudin J, Palanker D (2010) Strength-Duration Relationship for
Extracellular Neural Stimulation: Numerical and Analytical Models. J Neurophysiol
104:2236–2248. doi: 10.1152/jn.00343.2010
243. Brunel N, Van Rossum MCW (2007) Quantitative investigations of electrical nerve
excitation treated as polarization. Biol Cybern 97:341–349. doi: 10.1007/s00422-007-
0189-6
144
244. Chen W, Han Y, Chen Y, Astumian D (1998) Electric field-induced functional
reductions in the K+ channels mainly resulted from supramembrane potential-
mediated electroconformational changes. Biophys J 75:196–206. doi: 10.1016/S0006-
3495(98)77506-X
245. Chen W (2004) Supra-physiological membrane potential induced conformational
changes in K+ channel conducting system of skeletal muscle fibers.
Bioelectrochemistry 62:47–56. doi: 10.1016/j.bioelechem.2003.10.006
145
List of publications during Ph.D. candidature
Journal articles
1. Burke RC, Bardet SM, Carr L, et al (2017) Nanosecond pulsed electric fields
depolarize transmembrane potential via voltage-gated K+, Ca2+ and TRPM8 channels
in U87 glioblastoma cells. BBA - Biomembr 1859:2040–2050. doi:
10.1016/j.bbamem.2017.07.004
2. Carr L, Bardet SM, Burke RC, et al (2017) Calcium-independent disruption of
microtubule dynamics by nanosecond pulsed electric fields in U87 human
glioblastoma cells. Sci Rep. doi: 10.1038/srep41267
3. Moreau D, Lefort C, Burke R, et al (2015) Rhodamine B as an optical thermometer in
cells focally exposed to infrared laser light or nanosecond pulsed electric fields.
Biomed Opt Express 6:713–718. doi: 10.1364/BOE.6.004105
4. Dermol, Janja, Miklavcic, Damijan, Rebersek, Matej, et al (2017) Plasma membrane
depolarization and permeabilization due to electric pulses in cell lines of different
excitability. Bioelectrochemistry (in review)
146
Presentations at International Conferences
1. Burke R., Romanenko S., Moreau D., Arnaud-Cormos D., Leveque P., O'Connor R.P.
"Application of a voltage sensitive dye to study the effect of nanosecond pulsed
electric fields (nsPEF) on membrane potential in human U87 glioblastoma cells." In
BioEM 2015, Joint Meeting of the BioElectroMagnetics Society and the European
BioElectromagnetics Association, Pacific Grove, CA, USA, 14 - 19 June 2015
2. Burke, R., Moreau, David., Arnaud-Cormos, Delia., Leveque, Philippe., O’Connor,
Rodney. “Voltage-gated ion channel antagonists inhibit nsPEF-induced membrane
depolarization in U87 glioblastoma cells.” In EBTT 2015 proceedings, Ljubljana,
Slovenia, November 15 – 21, 2015.
3. Moreau, David., Lefort, Claire., Burke, Ryan., Leveque, Philippe., O’Connor,
Rodney. “Thermal effect of nanosecond pulsed electric fields.” In EBTT 2015
proceedings, Ljubljana, Slovenia, November 15 – 21, 2015.
4. Moreau, David., Lefort, Claire., Burke, Ryan., Leveque, Philippe., O’Connor,
Rodney. “Thermal imaging with Rhodamine B in cells exposed to electromagnetic
radiation.” In BioEM 2016, joint meeting of the Bioelectromagnetics Society and the
European Bioelectromagnetics Association, Ghent, Belgium, June 5 – 10, 2016.
5. Dermol, Janja., Arnaud-Cormos, Delia., Bardet, Sylvia., Burke, Ryan., Leveque,
Philippe., Mekuc, Primoz., Miklavcic, Damijan. “Cell membrane depolarization and
permeability of three cell lines of different excitability.” In BES 2017, XXIV
International symposium on Bioelectrochemistry and Bioenergetics of the
Bioelectrochemical Society, Lyon, France, July 3 – 7, 2017.
147
6. Frandsen, Stine., Burke, Ryan., Arnaud-Cormos, Delia., Bardet, Sylvia., Leveque,
Philippe. “Effect of in vitro calcium-electroporation on mitochondrial membrane
potential.” WC2017, 2nd World Congress on Electroporation and pulsed electric fields
in biology, medicine and food & environmental technologies, Norfolk, Virginia, USA,
September 24 – 28, 2017.
